Pdf ebook: Natural Language Processing with Python

Pdf download ebook Natural Language Processing with Python

Summary: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predicti

  • Author : N.a
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 0596555717
  • Genre: Computers
  • Number of Pages: 504
  • Language: English
  • Views: 1680
  • Downloads: 1680
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Description: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.


Pdf ebook: Hands-On Python Natural Language Processing

Pdf download ebook Hands-On Python Natural Language Processing

Summary: Get well-versed with traditional as well as modern natural language processing concepts and techniques Key Features Perform various NLP tasks to build ling

  • Author : Aman Kedia,Mayank Rasu
  • Publisher: Packt Publishing Ltd
  • ISBN: 1838982582
  • Genre: Computers
  • Number of Pages: 316
  • Language: English
  • Views: 1554
  • Downloads: 1554
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Description: Get well-versed with traditional as well as modern natural language processing concepts and techniques Key Features Perform various NLP tasks to build linguistic applications using Python libraries Understand, analyze, and generate text to provide accurate results Interpret human language using various NLP concepts, methodologies, and tools Book Description Natural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding. This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you’ll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own. By the end of this NLP book, you’ll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP. What you will learn Understand how NLP powers modern applications Explore key NLP techniques to build your natural language vocabulary Transform text data into mathematical data structures and learn how to improve text mining models Discover how various neural network architectures work with natural language data Get the hang of building sophisticated text processing models using machine learning and deep learning Check out state-of-the-art architectures that have revolutionized research in the NLP domain Who this book is for This NLP Python book is for anyone looking to learn NLP’s theoretical and practical aspects alike. It starts with the basics and gradually covers advanced concepts to make it easy to follow for readers with varying levels of NLP proficiency. This comprehensive guide will help you develop a thorough understanding of the NLP methodologies for building linguistic applications; however, working knowledge of Python programming language and high school level mathematics is expected.


Pdf ebook: Natural Language Processing with Python and spaCy

Pdf download ebook Natural Language Processing with Python and spaCy

Summary: An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library. Natural Language Processing w

  • Author : Yuli Vasiliev
  • Publisher: No Starch Press
  • ISBN: 171850053X
  • Genre: Computers
  • Number of Pages: 216
  • Language: English
  • Views: 1213
  • Downloads: 1213
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Description: An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library. Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: • Work with word vectors to mathematically find words with similar meanings (Chapter 5) • Identify patterns within data using spaCy's built-in displaCy visualizer (Chapter 7) • Automatically extract keywords from user input and store them in a relational database (Chapter 9) • Deploy a chatbot app to interact with users over the internet (Chapter 11) "Try This" sections in each chapter encourage you to practice what you've learned by expanding the book's example scripts to handle a wider range of inputs, add error handling, and build professional-quality applications. By the end of the book, you'll be creating your own NLP applications with Python and spaCy.


Pdf ebook: Python Natural Language Processing

Pdf download ebook Python Natural Language Processing

Summary: Leverage the power of machine learning and deep learning to extract information from text data About This Book Implement Machine Learning and Deep Learning

  • Author : Jalaj Thanaki
  • Publisher: Packt Publishing Ltd
  • ISBN: 1787285529
  • Genre: Computers
  • Number of Pages: 486
  • Language: English
  • Views: 1719
  • Downloads: 1719
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Description: Leverage the power of machine learning and deep learning to extract information from text data About This Book Implement Machine Learning and Deep Learning techniques for efficient natural language processing Get started with NLTK and implement NLP in your applications with ease Understand and interpret human languages with the power of text analysis via Python Who This Book Is For This book is intended for Python developers who wish to start with natural language processing and want to make their applications smarter by implementing NLP in them. What You Will Learn Focus on Python programming paradigms, which are used to develop NLP applications Understand corpus analysis and different types of data attribute. Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on Learn about Features Extraction and Feature selection as part of Features Engineering. Explore the advantages of vectorization in Deep Learning. Get a better understanding of the architecture of a rule-based system. Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems. Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems. In Detail This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world. Style and approach This book teaches the readers various aspects of natural language Processing using NLTK. It takes the reader from the basic to advance level in a smooth way.


Pdf ebook: Natural Language Processing with Python Quick Start Guide

Pdf download ebook Natural Language Processing with Python Quick Start Guide

Summary: Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep

  • Author : Nirant Kasliwal
  • Publisher: Packt Publishing Ltd
  • ISBN: 1788994108
  • Genre: Computers
  • Number of Pages: 182
  • Language: English
  • Views: 1304
  • Downloads: 1304
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Description: Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key Features A no-math, code-driven programmer’s guide to text processing and NLP Get state of the art results with modern tooling across linguistics, text vectors and machine learning Fundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorch Book Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learn Understand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpus Work with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clustering Deep Learning in NLP using PyTorch with a code-driven introduction to PyTorch Using an NLP project management Framework for estimating timelines and organizing your project into stages Hack and build a simple chatbot application in 30 minutes Deploy an NLP or machine learning application using Flask as RESTFUL APIs Who this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.


Pdf ebook: Hands-On Natural Language Processing with Python

Pdf download ebook Hands-On Natural Language Processing with Python

Summary: This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP cha

  • Author : Rajesh Arumugam,Rajalingappaa Shanmugamani
  • Publisher: Packt Publishing Ltd
  • ISBN: 1789135915
  • Genre: Computers
  • Number of Pages: 312
  • Language: English
  • Views: 1078
  • Downloads: 1078
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Description: This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. The book equips you with practical knowledge to implement deep learning in your linguistic applications using NLTk and Python's popular deep learning library, TensorFlow.


Pdf ebook: Python Natural Language Processing Cookbook

Pdf download ebook Python Natural Language Processing Cookbook

Summary: Leverage your natural language processing skills to make sense of text. With this book, you'll learn fundamental and advanced NLP techniques in Python that

  • Author : Zhenya Antić
  • Publisher: Packt Publishing Ltd
  • ISBN: 1838987789
  • Genre: Computers
  • Number of Pages: 284
  • Language: English
  • Views: 1434
  • Downloads: 1434
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Description: Leverage your natural language processing skills to make sense of text. With this book, you'll learn fundamental and advanced NLP techniques in Python that will help you to make your data fit for application in a wide variety of industries. You’ll also find recipes for overcoming common challenges in implementing NLP pipelines.


Pdf ebook: Natural Language Processing: Python and NLTK

Pdf download ebook Natural Language Processing: Python and NLTK

Summary: Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book Break text down into its component parts for

  • Author : Nitin Hardeniya,Jacob Perkins,Deepti Chopra,Nisheeth Joshi,Iti Mathur
  • Publisher: Packt Publishing Ltd
  • ISBN: 178728784X
  • Genre: Computers
  • Number of Pages: 687
  • Language: English
  • Views: 428
  • Downloads: 428
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Description: Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book Break text down into its component parts for spelling correction, feature extraction, and phrase transformation Work through NLP concepts with simple and easy-to-follow programming recipes Gain insights into the current and budding research topics of NLP Who This Book Is For If you are an NLP or machine learning enthusiast and an intermediate Python programmer who wants to quickly master NLTK for natural language processing, then this Learning Path will do you a lot of good. Students of linguistics and semantic/sentiment analysis professionals will find it invaluable. What You Will Learn The scope of natural language complexity and how they are processed by machines Clean and wrangle text using tokenization and chunking to help you process data better Tokenize text into sentences and sentences into words Classify text and perform sentiment analysis Implement string matching algorithms and normalization techniques Understand and implement the concepts of information retrieval and text summarization Find out how to implement various NLP tasks in Python In Detail Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: NTLK essentials by Nitin Hardeniya Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur Style and approach This comprehensive course creates a smooth learning path that teaches you how to get started with Natural Language Processing using Python and NLTK. You'll learn to create effective NLP and machine learning projects using Python and NLTK.


Pdf ebook: Natural Language Processing With Python

Pdf download ebook Natural Language Processing With Python

Summary: Natural Language Processing With Python This book is a perfect beginner's guide to natural language processing. It is offering an easy to understand guide

  • Author : Frank Millstein
  • Publisher: Frank Millstein
  • ISBN:
  • Genre: Computers
  • Number of Pages: 116
  • Language: English
  • Views: 1234
  • Downloads: 1234
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Description: Natural Language Processing With Python This book is a perfect beginner's guide to natural language processing. It is offering an easy to understand guide to implementing NLP techniques using Python. Natural language processing has been around for more than fifty years, but just recently with greater amounts of data present and better computational powers, it has gained a greater popularity. Given the importance of data, there is no wonder why natural language processing is on the rise. If you are interested in learning more, this book will serve as your best companion on this journey introducing you to this challenging, yet extremely engaging world of automatic manipulation of our human language. It covers all the basics you need to know before you dive deeper into NLP and solving more complex NLP tasks in Python. Here Is a Preview of What You’ll Learn Here… The main challenges of natural language processing The history of natural language processing How natural langauge processing actually works The main natural language processing applications Text preprocessing and noise removal Feature engineering and syntactic parsing Part of speech tagging and named entity extraction Topic modeling and word embedding Text classification problems Working with text data using NLTK Text summarization and sentiment analysis And much, much more... Get this book NOW and learn more about Natural Language Processing With Python!


Pdf ebook: Text Analytics with Python

Pdf download ebook Text Analytics with Python

Summary: Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition

  • Author : Dipanjan Sarkar
  • Publisher: Apress
  • ISBN: 1484243544
  • Genre: Computers
  • Number of Pages: 674
  • Language: English
  • Views: 635
  • Downloads: 635
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Description: Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.


Pdf ebook: Natural Language Processing in Action

Pdf download ebook Natural Language Processing in Action

Summary: Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosyste

  • Author : Hannes Hapke,Cole Howard,Hobson Lane
  • Publisher: Simon and Schuster
  • ISBN: 1638356890
  • Genre: Computers
  • Number of Pages: 544
  • Language: English
  • Views: 1149
  • Downloads: 1149
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Description: Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)


Pdf ebook: Natural Language Processing with TensorFlow

Pdf download ebook Natural Language Processing with TensorFlow

Summary: Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language

  • Author : Thushan Ganegedara
  • Publisher: Packt Publishing Ltd
  • ISBN: 1788477758
  • Genre: Computers
  • Number of Pages: 472
  • Language: English
  • Views: 1891
  • Downloads: 1891
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Description: Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful.


Pdf ebook: Natural Language Processing and Computational Linguistics

Pdf download ebook Natural Language Processing and Computational Linguistics

Summary: Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational li

  • Author : Bhargav Srinivasa-Desikan
  • Publisher: Packt Publishing Ltd
  • ISBN: 1788837037
  • Genre: Computers
  • Number of Pages: 306
  • Language: English
  • Views: 595
  • Downloads: 595
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Description: Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!


Pdf ebook: Natural Language Processing Fundamentals

Pdf download ebook Natural Language Processing Fundamentals

Summary: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features Assimilate key NLP concep

  • Author : Sohom Ghosh,Dwight Gunning
  • Publisher: Packt Publishing Ltd
  • ISBN: 178995598X
  • Genre: Computers
  • Number of Pages: 374
  • Language: English
  • Views: 745
  • Downloads: 745
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Description: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features Assimilate key NLP concepts and terminologies Explore popular NLP tools and techniques Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn Obtain, verify, and clean data before transforming it into a correct format for use Perform data analysis and machine learning tasks using Python Understand the basics of computational linguistics Build models for general natural language processing tasks Evaluate the performance of a model with the right metrics Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.


Pdf ebook: Natural Language Processing Recipes

Pdf download ebook Natural Language Processing Recipes

Summary: Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help yo

  • Author : Akshay Kulkarni,Adarsha Shivananda
  • Publisher: Apress
  • ISBN: 148424267X
  • Genre: Computers
  • Number of Pages: 234
  • Language: English
  • Views: 1048
  • Downloads: 1048
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Description: Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing. By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient. What You Will Learn Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques. Identify machine learning and deep learning techniques for natural language processing and natural language generation problems Who This Book Is ForData scientists who want to refresh and learn various concepts of natural language processing through coding exercises.


Pdf ebook: Deep Learning for Natural Language Processing

Pdf download ebook Deep Learning for Natural Language Processing

Summary: Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent ne

  • Author : Palash Goyal,Sumit Pandey,Karan Jain
  • Publisher: Apress
  • ISBN: 1484236858
  • Genre: Computers
  • Number of Pages: 277
  • Language: English
  • Views: 1577
  • Downloads: 1577
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Description: Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. What You Will Learn Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification Who This Book Is For Software developers who are curious to try out deep learning with NLP.


Pdf ebook: Natural Language Processing with PyTorch

Pdf download ebook Natural Language Processing with PyTorch

Summary: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa an

  • Author : Delip Rao,Brian McMahan
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 149197818X
  • Genre: Computers
  • Number of Pages: 256
  • Language: English
  • Views: 1889
  • Downloads: 1889
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Description: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems


Pdf ebook: Transformers for Natural Language Processing

Pdf download ebook Transformers for Natural Language Processing

Summary: Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the perform

  • Author : Denis Rothman
  • Publisher: Packt Publishing Ltd
  • ISBN: 1800568630
  • Genre: Computers
  • Number of Pages: 384
  • Language: English
  • Views: 1766
  • Downloads: 1766
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Description: Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers using PyTorch, TensorFlow, Hugging Face, Trax, and AllenNLP.


Pdf ebook: Building Chatbots with Python

Pdf download ebook Building Chatbots with Python

Summary: Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their

  • Author : Sumit Raj
  • Publisher: Apress
  • ISBN: 1484240960
  • Genre: Computers
  • Number of Pages: 192
  • Language: English
  • Views: 545
  • Downloads: 545
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Description: Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you. The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment. The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learn to predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS. What You Will Learn Gain the basics of natural language processing using Python Collect data and train your data for the chatbot Build your chatbot from scratch as a web app Integrate your chatbots with Facebook, Slack, and Telegram Deploy chatbots on your own server Who This Book Is For Intermediate Python developers who have no idea about chatbots. Developers with basic Python programming knowledge can also take advantage of the book.


Pdf ebook: Introduction to Natural Language Processing

Pdf download ebook Introduction to Natural Language Processing

Summary: A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and

  • Author : Jacob Eisenstein
  • Publisher: MIT Press
  • ISBN: 0262354578
  • Genre: Computers
  • Number of Pages: 536
  • Language: English
  • Views: 1500
  • Downloads: 1500
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Description: A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.


Pdf ebook: The Natural Language Processing Workshop

Pdf download ebook The Natural Language Processing Workshop

Summary: Make NLP easy by building chatbots and models, and executing various NLP tasks to gain data-driven insights from raw text data Key Features Get familiar wi

  • Author : Rohan Chopra,Aniruddha M. Godbole,Nipun Sadvilkar,Muzaffar Bashir Shah,Sohom Ghosh,Dwight Gunning
  • Publisher: Packt Publishing Ltd
  • ISBN: 1800200803
  • Genre: Computers
  • Number of Pages: 452
  • Language: English
  • Views: 1250
  • Downloads: 1250
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Description: Make NLP easy by building chatbots and models, and executing various NLP tasks to gain data-driven insights from raw text data Key Features Get familiar with key natural language processing (NLP) concepts and terminology Explore the functionalities and features of popular NLP tools Learn how to use Python programming and third-party libraries to perform NLP tasks Book Description Do you want to learn how to communicate with computer systems using Natural Language Processing (NLP) techniques, or make a machine understand human sentiments? Do you want to build applications like Siri, Alexa, or chatbots, even if you've never done it before? With The Natural Language Processing Workshop, you can expect to make consistent progress as a beginner, and get up to speed in an interactive way, with the help of hands-on activities and fun exercises. The book starts with an introduction to NLP. You'll study different approaches to NLP tasks, and perform exercises in Python to understand the process of preparing datasets for NLP models. Next, you'll use advanced NLP algorithms and visualization techniques to collect datasets from open websites, and to summarize and generate random text from a document. In the final chapters, you'll use NLP to create a chatbot that detects positive or negative sentiment in text documents such as movie reviews. By the end of this book, you'll be equipped with the essential NLP tools and techniques you need to solve common business problems that involve processing text. What you will learn Obtain, verify, clean and transform text data into a correct format for use Use methods such as tokenization and stemming for text extraction Develop a classifier to classify comments in Wikipedia articles Collect data from open websites with the help of web scraping Train a model to detect topics in a set of documents using topic modeling Discover techniques to represent text as word and document vectors Who this book is for This book is for beginner to mid-level data scientists, machine learning developers, and NLP enthusiasts. A basic understanding of machine learning and NLP is required to help you grasp the topics in this workshop more quickly.


Pdf ebook: Real-World Natural Language Processing

Pdf download ebook Real-World Natural Language Processing

Summary: Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work togeth

  • Author : Masato Hagiwara
  • Publisher: Simon and Schuster
  • ISBN: 1638350396
  • Genre: Computers
  • Number of Pages: 336
  • Language: English
  • Views: 1473
  • Downloads: 1473
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Description: Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. In Real-world Natural Language Processing you will learn how to: Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots Use advanced NLP concepts such as attention and transfer learning Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps, including chatbots, language detectors, and text classifiers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! Th e field of Natural Language Processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assistants, text generation, and more. About the book Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you’ll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process. What's inside Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots About the reader For Python programmers. No prior machine learning knowledge assumed. About the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009. He has interned at Google and Microsoft Research, and worked at Duolingo as a Senior Machine Learning Engineer. He now runs his own research and consulting company. Table of Contents PART 1 BASICS 1 Introduction to natural language processing 2 Your first NLP application 3 Word and document embeddings 4 Sentence classification 5 Sequential labeling and language modeling PART 2 ADVANCED MODELS 6 Sequence-to-sequence models 7 Convolutional neural networks 8 Attention and Transformer 9 Transfer learning with pretrained language models PART 3 PUTTING INTO PRODUCTION 10 Best practices in developing NLP applications 11 Deploying and serving NLP applications


Pdf ebook: Deep Learning for Natural Language Processing

Pdf download ebook Deep Learning for Natural Language Processing

Summary: Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key Features Gain insights into the

  • Author : Karthiek Reddy Bokka,Shubhangi Hora,Tanuj Jain,Monicah Wambugu
  • Publisher: Packt Publishing Ltd
  • ISBN: 1838553673
  • Genre: Computers
  • Number of Pages: 372
  • Language: English
  • Views: 1229
  • Downloads: 1229
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Description: Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key Features Gain insights into the basic building blocks of natural language processing Learn how to select the best deep neural network to solve your NLP problems Explore convolutional and recurrent neural networks and long short-term memory networks Book Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learn Understand various pre-processing techniques for deep learning problems Build a vector representation of text using word2vec and GloVe Create a named entity recognizer and parts-of-speech tagger with Apache OpenNLP Build a machine translation model in Keras Develop a text generation application using LSTM Build a trigger word detection application using an attention model Who this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.


Pdf ebook: Applied Text Analysis with Python

Pdf download ebook Applied Text Analysis with Python

Summary: From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it

  • Author : Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491962992
  • Genre: Computers
  • Number of Pages: 332
  • Language: English
  • Views: 1965
  • Downloads: 1965
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Description: From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity


Pdf ebook: Python 3 Text Processing with NLTK 3 Cookbook

Pdf download ebook Python 3 Text Processing with NLTK 3 Cookbook

Summary: This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular exp

  • Author : Jacob Perkins
  • Publisher: Packt Publishing Ltd
  • ISBN: 1782167862
  • Genre: Computers
  • Number of Pages: 304
  • Language: English
  • Views: 399
  • Downloads: 399
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Description: This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular expressions the hard way, or you’ve realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.


Pdf ebook: Efficient Processing of Deep Neural Networks

Pdf download ebook Efficient Processing of Deep Neural Networks

Summary: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are c

  • Author : Vivienne Sze,Yu-Hsin Chen,Tien-Ju Yang,Joel S. Emer
  • Publisher: Morgan & Claypool Publishers
  • ISBN: 1681738325
  • Genre: Computers
  • Number of Pages: 341
  • Language: English
  • Views: 1639
  • Downloads: 1639
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Description: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of the DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as a formalization and organization of key concepts from contemporary works that provides insights that may spark new ideas.


Pdf ebook: Mining the Social Web

Pdf download ebook Mining the Social Web

Summary: Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s ma

  • Author : Matthew A. Russell
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449303935
  • Genre: Computers
  • Number of Pages: 356
  • Language: English
  • Views: 1957
  • Downloads: 1957
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Description: Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s making connections with social media, what they’re talking about, and where they’re located. You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+ Learn how to employ easy-to-use Python tools to slice and dice the data you collect Explore social connections in microformats with the XHTML Friends Network Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits "A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google


Pdf ebook: Natural Language Processing Fundamentals for Developers

Pdf download ebook Natural Language Processing Fundamentals for Developers

Summary: This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help dev

  • Author : Oswald Campesato
  • Publisher: Stylus Publishing, LLC
  • ISBN: 1683926552
  • Genre: Computers
  • Number of Pages: 500
  • Language: English
  • Views: 772
  • Downloads: 772
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Description: This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter shows you various details of managing data that are relevant for NLP. The next pair of chapters contain NLP concepts, followed by another pair of chapters with Python code samples to illustrate those NLP concepts. Chapter 6 explores applications, e.g., sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and a short discussion regarding chatbots. The final chapter presents the Transformer architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years and considered SOTA (“state of the art”). The appendices contain introductory material (including Python code samples) on regular expressions and probability/statistical concepts. Companion files with source code and figures are included. FEATURES: Covers extensive topics related to natural language processing Includes separate appendices on regular expressions and probability/statistics Features companion files with source code and figures from the book.


Pdf ebook: Chemical Engineering Design

Pdf download ebook Chemical Engineering Design

Summary: Chemical Engineering Design, Second Edition, deals with the application of chemical engineering principles to the design of chemical processes and equipmen

  • Author : Gavin Towler,Ray Sinnott
  • Publisher: Elsevier
  • ISBN: 0080966608
  • Genre: Technology & Engineering
  • Number of Pages: 1320
  • Language: English
  • Views: 1690
  • Downloads: 1690
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Description: Chemical Engineering Design, Second Edition, deals with the application of chemical engineering principles to the design of chemical processes and equipment. Revised throughout, this edition has been specifically developed for the U.S. market. It provides the latest US codes and standards, including API, ASME and ISA design codes and ANSI standards. It contains new discussions of conceptual plant design, flowsheet development, and revamp design; extended coverage of capital cost estimation, process costing, and economics; and new chapters on equipment selection, reactor design, and solids handling processes. A rigorous pedagogy assists learning, with detailed worked examples, end of chapter exercises, plus supporting data, and Excel spreadsheet calculations, plus over 150 Patent References for downloading from the companion website. Extensive instructor resources, including 1170 lecture slides and a fully worked solutions manual are available to adopting instructors. This text is designed for chemical and biochemical engineering students (senior undergraduate year, plus appropriate for capstone design courses where taken, plus graduates) and lecturers/tutors, and professionals in industry (chemical process, biochemical, pharmaceutical, petrochemical sectors). New to this edition: Revised organization into Part I: Process Design, and Part II: Plant Design. The broad themes of Part I are flowsheet development, economic analysis, safety and environmental impact and optimization. Part II contains chapters on equipment design and selection that can be used as supplements to a lecture course or as essential references for students or practicing engineers working on design projects. New discussion of conceptual plant design, flowsheet development and revamp design Significantly increased coverage of capital cost estimation, process costing and economics New chapters on equipment selection, reactor design and solids handling processes New sections on fermentation, adsorption, membrane separations, ion exchange and chromatography Increased coverage of batch processing, food, pharmaceutical and biological processes All equipment chapters in Part II revised and updated with current information Updated throughout for latest US codes and standards, including API, ASME and ISA design codes and ANSI standards Additional worked examples and homework problems The most complete and up to date coverage of equipment selection 108 realistic commercial design projects from diverse industries A rigorous pedagogy assists learning, with detailed worked examples, end of chapter exercises, plus supporting data and Excel spreadsheet calculations plus over 150 Patent References, for downloading from the companion website Extensive instructor resources: 1170 lecture slides plus fully worked solutions manual available to adopting instructors


Pdf ebook: Advanced Natural Language Processing with TensorFlow 2

Pdf download ebook Advanced Natural Language Processing with TensorFlow 2

Summary: This book provides hands-on training in NLP tools and techniques with intrinsic details. Apart from gaining expertise, you will be able to carry out novel

  • Author : Ashish Bansal
  • Publisher: Packt Publishing Ltd
  • ISBN: 1800201052
  • Genre: Computers
  • Number of Pages: 380
  • Language: English
  • Views: 942
  • Downloads: 942
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Description: This book provides hands-on training in NLP tools and techniques with intrinsic details. Apart from gaining expertise, you will be able to carry out novel state-of-the-art research using the skills gained.


Pdf ebook: Leveraging Data Science for Global Health

Pdf download ebook Leveraging Data Science for Global Health

Summary: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-co

  • Author : Leo Anthony Celi,Maimuna S. Majumder,Patricia Ordóñez,Juan Sebastian Osorio,Kenneth E. Paik,Melek Somai
  • Publisher: Springer Nature
  • ISBN: 3030479943
  • Genre: Medical
  • Number of Pages: 475
  • Language: English
  • Views: 1499
  • Downloads: 1499
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Description: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.


Pdf ebook: Linguistic Fundamentals for Natural Language Processing

Pdf download ebook Linguistic Fundamentals for Natural Language Processing

Summary: Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be under

  • Author : Emily M. Bender
  • Publisher: Morgan & Claypool Publishers
  • ISBN: 1627050124
  • Genre: Computers
  • Number of Pages: 184
  • Language: English
  • Views: 696
  • Downloads: 696
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Description: Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages


Pdf ebook: Neural Networks for Natural Language Processing

Pdf download ebook Neural Networks for Natural Language Processing

Summary: Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time

  • Author : S., Sumathi,M., Janani
  • Publisher: IGI Global
  • ISBN: 1799811611
  • Genre: Computers
  • Number of Pages: 227
  • Language: English
  • Views: 1127
  • Downloads: 1127
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Description: Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.


Pdf ebook: Derinlemesine Python AI Natural Language Processing

Pdf download ebook Derinlemesine Python AI Natural Language Processing

Summary: Bu kitapta Python ile Artificial Ingelligence & Machine Learning anlatılmaktadır. Clustering, Classification & Regression gibi konular işlenmektedir. Ar

  • Author : Önder Teker
  • Publisher: Godoro
  • ISBN: 6057476409
  • Genre: Computers
  • Number of Pages: 290
  • Language: English
  • Views: 1414
  • Downloads: 1414
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Description: Bu kitapta Python ile Artificial Ingelligence & Machine Learning anlatılmaktadır. Clustering, Classification & Regression gibi konular işlenmektedir. Artificial Neural Networks, Support Vectors, DecisionTree, K-Nearest Neighbours, K-Means yöntemleri açıklanmaktadır. Gerçek veri ve Tk arayüzü uygulamaları da kapsamdadır. Skit-Learn ile konular işlenip TensorFlow & Keras ile PyTorch kütüphaneleri de anlatılmaktadır.


Pdf ebook: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Pdf download ebook Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Summary: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing a

  • Author : Aurélien Géron
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 149203259X
  • Genre: Computers
  • Number of Pages: 856
  • Language: English
  • Views: 1262
  • Downloads: 1262
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Description: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets


Pdf ebook: Deep Learning in Natural Language Processing

Pdf download ebook Deep Learning in Natural Language Processing

Summary: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural

  • Author : Li Deng,Yang Liu
  • Publisher: Springer
  • ISBN: 9811052093
  • Genre: Computers
  • Number of Pages: 329
  • Language: English
  • Views: 1417
  • Downloads: 1417
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Description: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.


Pdf ebook: Foundations of Statistical Natural Language Processing

Pdf download ebook Foundations of Statistical Natural Language Processing

Summary: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduc

  • Author : Christopher Manning,Hinrich Schutze
  • Publisher: MIT Press
  • ISBN: 0262303795
  • Genre: Language Arts & Disciplines
  • Number of Pages: 720
  • Language: English
  • Views: 1611
  • Downloads: 1611
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Description: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.


Pdf ebook: Getting Started with Google BERT

Pdf download ebook Getting Started with Google BERT

Summary: Getting Started with Google BERT will help you become well-versed with the BERT model from scratch and learn how to create interesting NLP applications. Yo

  • Author : Sudharsan Ravichandiran
  • Publisher: Packt Publishing Ltd
  • ISBN: 1838826238
  • Genre: Computers
  • Number of Pages: 352
  • Language: English
  • Views: 910
  • Downloads: 910
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Description: Getting Started with Google BERT will help you become well-versed with the BERT model from scratch and learn how to create interesting NLP applications. You'll understand several variants of BERT such as ALBERT, RoBERTa, DistilBERT, ELECTRA, VideoBERT, and many others in detail.


Pdf ebook: Neural Network Methods in Natural Language Processing

Pdf download ebook Neural Network Methods in Natural Language Processing

Summary: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. T

  • Author : Yoav Goldberg
  • Publisher: Morgan & Claypool Publishers
  • ISBN: 162705295X
  • Genre: Computers
  • Number of Pages: 309
  • Language: English
  • Views: 736
  • Downloads: 736
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Description: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.


Pdf ebook: Text Mining with R

Pdf download ebook Text Mining with R

Summary: Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization t

  • Author : Julia Silge,David Robinson
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491981601
  • Genre: Computers
  • Number of Pages: 194
  • Language: English
  • Views: 628
  • Downloads: 628
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Description: Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document’s most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R’s tidy and non-tidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages