The Nlp Cookbook

Author : Zhenya Antić
Publisher : Packt Publishing Ltd
ISBN 13 : 1838987789
Total Pages : 285 pages
Book Rating : 4.87/5 ( download)

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Download or read book Python Natural Language Processing Cookbook written by Zhenya Antić and published by Packt Publishing Ltd. This book was released on 2021-03-19 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualization Key FeaturesAnalyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensimImplement common and not-so-common linguistic processing tasks using Python librariesOvercome the common challenges faced while implementing NLP pipelinesBook Description Python is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization. Starting with an overview of NLP, the book presents recipes for dividing text into sentences, stemming and lemmatization, removing stopwords, and parts of speech tagging to help you to prepare your data. You’ll then learn ways of extracting and representing grammatical information, such as dependency parsing and anaphora resolution, discover different ways of representing the semantics using bag-of-words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques. As you advance, you’ll also see how to extract information from text, implement unsupervised and supervised techniques for topic modeling, and perform topic modeling of short texts, such as tweets. Additionally, the book shows you how to develop chatbots using NLTK and Rasa and visualize text data. By the end of this NLP book, you’ll have developed the skills to use a powerful set of tools for text processing. What you will learnBecome well-versed with basic and advanced NLP techniques in PythonRepresent grammatical information in text using spaCy, and semantic information using bag-of-words, TF-IDF, and word embeddingsPerform text classification using different methods, including SVMs and LSTMsExplore different techniques for topic modeling such as K-means, LDA, NMF, and BERTWork with visualization techniques such as NER and word clouds for different NLP toolsBuild a basic chatbot using NLTK and RasaExtract information from text using regular expression techniques and statistical and deep learning toolsWho this book is for This book is for data scientists and professionals who want to learn how to work with text. Intermediate knowledge of Python will help you to make the most out of this book. If you are an NLP practitioner, this book will serve as a code reference when working on your projects.

Author : Steven Bird
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 0596555717
Total Pages : 506 pages
Book Rating : 4.19/5 ( download)

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Download or read book Natural Language Processing with Python written by Steven Bird and published by "O'Reilly Media, Inc.". This book was released on 2009-06-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Lewis Tunstall
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098136764
Total Pages : 409 pages
Book Rating : 4.65/5 ( download)

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Download or read book Natural Language Processing with Transformers, Revised Edition written by Lewis Tunstall and published by "O'Reilly Media, Inc.". This book was released on 2022-05-26 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments

Author : Sowmya Vajjala
Publisher : O'Reilly Media
ISBN 13 : 149205402X
Total Pages : 455 pages
Book Rating : 4.23/5 ( download)

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Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Author : Richard M. Reese
Publisher : Packt Publishing Ltd
ISBN 13 : 1789808839
Total Pages : 374 pages
Book Rating : 4.34/5 ( download)

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Download or read book Natural Language Processing with Java Cookbook written by Richard M. Reese and published by Packt Publishing Ltd. This book was released on 2019-04-25 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key FeaturesPerform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operationsBook Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learnExplore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within the text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languagesWho this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.

Author : Akshay Kulkarni
Publisher : Apress
ISBN 13 : 148424267X
Total Pages : 253 pages
Book Rating : 4.74/5 ( download)

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Download or read book Natural Language Processing Recipes written by Akshay Kulkarni and published by Apress. This book was released on 2019-01-29 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 LearnApply 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.

Author : Krishna Bhavsar
Publisher :
ISBN 13 : 9781787289321
Total Pages : 316 pages
Book Rating : 4.2X/5 ( download)

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Download or read book Natural Language Processing with Python Cookbook written by Krishna Bhavsar and published by . This book was released on 2017-11-24 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the tricks and tips that will help you design Text Analytics solutionsAbout This Book* Independent recipes that will teach you how to efficiently perform Natural Language Processing in Python* Use dictionaries to create your own named entities using this easy-to-follow guide* Learn how to implement NLTK for various scenarios with the help of example-rich recipes to take you beyond basic Natural Language ProcessingWho This Book Is ForThis book is intended for data scientists, data analysts, and data science professionals who want to upgrade their existing skills to implement advanced text analytics using NLP. Some basic knowledge of Natural Language Processing is recommended.What You Will Learn* Explore corpus management using internal and external corpora* Learn WordNet usage and a couple of simple application assignments using WordNet* Operate on raw text* Learn to perform tokenization, stemming, lemmatization, and spelling corrections, stop words removals, and more* Understand regular expressions for pattern matching* Learn to use and write your own POS taggers and grammars* Learn to evaluate your own trained models* Explore Deep Learning techniques in NLP* Generate Text from Nietzsche's writing using LSTM* Utilize the BABI dataset and LSTM to model episodesIn DetailNatural Language Processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages; in particular, it's about programming computers to fruitfully process large natural language corpora.This book includes unique recipes that will teach you various aspects of performing Natural Language Processing with NLTK-the leading Python platform for the task. You will come across various recipes during the course, covering (among other topics) natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to understand language, plan sentences, and work around various ambiguities. You will learn how to efficiently use NLTK and implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master lexical analysis, syntactic and semantic analysis, pragmatic analysis, and the application of deep learning techniques.By the end of this book, you will have all the knowledge you need to implement Natural Language Processing with Python.Style and ApproachThis book's rich collection of recipes will come in handy when you are working with Natural Language Processing with Python. Addressing your common and not-so-common pain points, this is a book that you must have on the shelf.

Author : Fran Burgess
Publisher : Crown House Publishing
ISBN 13 : 1845908422
Total Pages : 321 pages
Book Rating : 4.23/5 ( download)

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Download or read book The NLP Cookbook written by Fran Burgess and published by Crown House Publishing. This book was released on 2011-11-16 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NLP Cookbook is a veritable smorgasbord of NLP and related techniques gleaned from some of the greatest names in the field and adapted to provide an encyclopaedic resource for all therapists, coaches, change agents or health professionals.Fran Burgess uses the metaphor of cooking to describe the process of bringing together the best ingredients in NLP and selecting them carefully in order to produce some mouth watering results. The recipes are grouped into sections depending on their purpose. Quite a few focus on how to shift state, with some of these targeting specific states like acceptance and anxiety. These are followed by recipes that seek to develop behaviours and skills, and others that address beliefs and identity. There is then a wide range to choose from which deal with goals, relationships and the process of change.The beauty is that most of them can be used time and again for different circumstances and contexts, so they never wear out. Each recipe is prefaced by an introduction, giving you some background to its source and evolution. You are provided with its ingredients, should you be interested in its engineering, plus timings and materials required, and if it is suitable for working solo, or with a partner. Novice cooks can follow the recipes slavishly whereas those with more experience can adapt a recipe, adding a little something here, removing a little something there. This is not magic. They understand the chemistry that underpins the cooking process. They know what happens when you put this with that, now or later.

Author : Nitin Hardeniya
Publisher : Packt Publishing Ltd
ISBN 13 : 178728784X
Total Pages : 687 pages
Book Rating : 4.46/5 ( download)

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Download or read book Natural Language Processing: Python and NLTK written by Nitin Hardeniya and published by Packt Publishing Ltd. This book was released on 2016-11-22 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Delip Rao
Publisher : O'Reilly Media
ISBN 13 : 1491978201
Total Pages : 256 pages
Book Rating : 4.07/5 ( download)

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Download or read book Natural Language Processing with PyTorch written by Delip Rao and published by O'Reilly Media. This book was released on 2019-01-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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