Python For Natural Language Processing
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Natural Language Processing With Python
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Author : Steven Bird
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2009-06-12
Natural Language Processing With Python written by Steven Bird and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-12 with Computers categories.
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.
Natural Language Understanding With Python
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Author : Deborah A. Dahl
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30
Natural Language Understanding With Python written by Deborah A. Dahl and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.
Build advanced NLU systems by utilizing NLP libraries such as NLTK, SpaCy, BERT, and OpenAI; ML libraries like Keras, scikit-learn, pandas, TensorFlow, and NumPy, along with visualization libraries such as Matplotlib and Seaborn. Purchase of the print Kindle book includes a free PDF eBook Key Features Master NLU concepts from basic text processing to advanced deep learning techniques Explore practical NLU applications like chatbots, sentiment analysis, and language translation Gain a deeper understanding of large language models like ChatGPT Book DescriptionNatural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications. with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future. By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.What you will learn Explore the uses and applications of different NLP techniques Understand practical data acquisition and system evaluation workflows Build cutting-edge and practical NLP applications to solve problems Master NLP development from selecting an application to deployment Optimize NLP application maintenance after deployment Build a strong foundation in neural networks and deep learning for NLU Who this book is for This book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
Natural Language Processing With Python
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Author : Frank Millstein
language : en
Publisher: Frank Millstein
Release Date : 2020-07-06
Natural Language Processing With Python written by Frank Millstein and has been published by Frank Millstein this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-06 with Computers categories.
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!
Natural Language Processing Recipes
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Author : Akshay Kulkarni
language : en
Publisher: Apress
Release Date : 2019-01-29
Natural Language Processing Recipes written by Akshay Kulkarni and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Computers categories.
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 thisbook, 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.
Natural Language Processing With Python Cookbook
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Author : Krishna Bhavsar
language : en
Publisher:
Release Date : 2017-11-24
Natural Language Processing With Python Cookbook written by Krishna Bhavsar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-24 with Computers categories.
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.
Natural Language Processing In Action
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Author : Hannes Hapke
language : en
Publisher: Simon and Schuster
Release Date : 2019-03-16
Natural Language Processing In Action written by Hannes Hapke and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Computers categories.
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)
Natural Language Processing And Computational Linguistics
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Author : Bhargav Srinivasa-Desikan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-29
Natural Language Processing And Computational Linguistics written by Bhargav Srinivasa-Desikan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.
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!
Natural Language Processing With Python And Spacy
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Author : Yuli Vasiliev
language : en
Publisher: No Starch Press
Release Date : 2020-05-12
Natural Language Processing With Python And Spacy written by Yuli Vasiliev and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-12 with Computers categories.
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.
Natural Language Processing
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Author : Samuel Burns
language : en
Publisher:
Release Date : 2019-07-08
Natural Language Processing written by Samuel Burns and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-08 with categories.
Natural language processing (NLP) is about developing applications and services that are able to understand human languages. In this perfect Natural Language Processing Tutorial, we will use Python NLTK library. Natural language toolkit (NLTK) is the most popular library for natural language processing (NLP) which was written in Python and has a big community behind it. This is the Ultimate guide to learn Natural Language Processing (NLP) basics, such as how to identify and separate words, how to extract topics in a text. You dont need a big and a boring book to start today .So Get Your Copy Now!!Book ObjectivesThe book objectives include the following: To help you appreciate big data as a great source of information and knowledge. To help you understand natural language processing. To help you know how to use natural language processing to extract knowledge and information from big data. To help you learn how to implement natural language processing solutions using NLTK (Natural Language Processing Toolkit) and other libraries in Python. Who this Book is for? Do you belong to any of the following categories? You are a complete beginner to natural language processing. You want to learn Python programming for natural language processing. You want to advance your skills in Python for natural language processing. Professors, lecturers or tutors who are looking to find better ways to explain Natural Language Processing to their students in the simplest and easiest way. Students and academicians, especially those focusing on python programming, Neural Networks, Machine Learning, Deep Learning, and Artificial Intelligence. If yes, this is the right book for you. What do you need for this Book? You only have to have installed Python 3.X on your computer. The author guides you on how to install the rest of the libraries on your computer. What is inside the book? GETTING STARTED WITH NATURAL LANGUAGE PROCESSING TEXT WRANGLING AND CLEANSING. REPLACING AND CORRECTING WORDS. TEXT CLASSIFICATION. SENTIMENT ANALYSIS. PARSING STRUCTURE IN TEXT. SOCIAL MEDIA MINING. NLTK FOR SENTIMENT ANALYSIS. SCIKIT-LEARN FOR TEXT CLASSIFICATION. WORK WITH PDF FILES IN PYTHON. WORK WITH TEXT FILES IN PYTHON. WORD2VEC ALGORITHM. NLP APPLICATIONS From the back cover.This comprehensive guide covers both statistical and symbolic approaches to Natural Language Processing. This is a good introduction to all the major topics of computational linguistics, which includes automatic speech recognition and processing, machine translation, information extraction, and statistical methods of linguistic analysis. Indeed, Natural Language Processing is the scientific discipline concerned with making the natural language accessible to machines, and it is a necessary means to facilitate text analytics by establishing structure in unstructured text to enable further analysis. This guide is a fundamental reference for any computational linguist, speech scientist or language data scientist. The explanations and illustrations in this short book are very intuitive and simple. The author helps you understand what natural language processing is. This is basically a theory touching on the fundamentals of natural language processing. The author then explains to you what the NLTK library is and what it does. The rest of the book is about implementing natural language processing tasks using the NLTK library in Python. Samuel Burns uses a combination of theory, Python code examples, and screenshots showing the expected outputs for various program codes.
Natural Language Processing Crash Course For Beginners
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Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-08-04
Natural Language Processing Crash Course For Beginners written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with categories.
Natural Language Processing Crash Course for Beginners Artificial Intelligence (AI) isn't the latest fad! The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings. How Is This Book Different? This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder. The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning. Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing? Environment Setup and Python Crash Course Introduction to Deep Learning Text Cleaning and Manipulation Common NLP Tasks Importing Text Data from Various Sources Word Embeddings: Converting Words to Numbers IMDB Movies Sentimental Analysis Ham and Spam Message Classification Text Summarization and Topic Modeling Text Classification with Deep Learning Text Translation Using Seq2Seq Model State of the Art NLP with BERT Transformers Hands-on NLP Projects/Articles for Practice Exercise Solutions Click the BUY button and download the book now to start your Natural Language Processing journey.