Python Natural Language Processing Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1838987789
Total Pages : 285 pages
Book Rating : 4.8/5 (389 download)

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Book Synopsis Python Natural Language Processing Cookbook by : Zhenya Antić

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 Features Analyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensim Implement common and not-so-common linguistic processing tasks using Python libraries Overcome the common challenges faced while implementing NLP pipelines Book DescriptionPython 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 learn Become well-versed with basic and advanced NLP techniques in Python Represent grammatical information in text using spaCy, and semantic information using bag-of-words, TF-IDF, and word embeddings Perform text classification using different methods, including SVMs and LSTMs Explore different techniques for topic modeling such as K-means, LDA, NMF, and BERT Work with visualization techniques such as NER and word clouds for different NLP tools Build a basic chatbot using NLTK and Rasa Extract information from text using regular expression techniques and statistical and deep learning tools Who 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.

Natural Language Processing with Python

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 0596555717
Total Pages : 506 pages
Book Rating : 4.5/5 (965 download)

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Book Synopsis Natural Language Processing with Python by : Steven Bird

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.

Practical Natural Language Processing

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Publisher : O'Reilly Media
ISBN 13 : 149205402X
Total Pages : 455 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical Natural Language Processing by : Sowmya Vajjala

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

The NLP Cookbook

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Publisher : Crown House Publishing
ISBN 13 : 1845908422
Total Pages : 321 pages
Book Rating : 4.8/5 (459 download)

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Book Synopsis The NLP Cookbook by : Fran Burgess

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.

Natural Language Processing with Transformers, Revised Edition

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098136764
Total Pages : 409 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Natural Language Processing with Transformers, Revised Edition by : Lewis Tunstall

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

Natural Language Processing with Python Cookbook

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Publisher :
ISBN 13 : 9781787289321
Total Pages : 316 pages
Book Rating : 4.2/5 (893 download)

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Book Synopsis Natural Language Processing with Python Cookbook by : Krishna Bhavsar

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.

Hands-On Natural Language Processing with Python

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789135915
Total Pages : 307 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Hands-On Natural Language Processing with Python by : Rajesh Arumugam

Download or read book Hands-On Natural Language Processing with Python written by Rajesh Arumugam and published by Packt Publishing Ltd. This book was released on 2018-07-18 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Natural Language Processing with Java Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789808839
Total Pages : 374 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Natural Language Processing with Java Cookbook by : Richard M. Reese

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.

Natural Language Processing: Python and NLTK

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Publisher : Packt Publishing Ltd
ISBN 13 : 178728784X
Total Pages : 687 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Natural Language Processing: Python and NLTK by : Nitin Hardeniya

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.

Natural Language Processing Recipes

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Publisher : Apress
ISBN 13 : 148424267X
Total Pages : 253 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Natural Language Processing Recipes by : Akshay Kulkarni

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.

Python Natural Language Processing

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Publisher : Packt Publishing Ltd
ISBN 13 : 1787285529
Total Pages : 476 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Python Natural Language Processing by : Jalaj Thanaki

Download or read book Python Natural Language Processing written by Jalaj Thanaki and published by Packt Publishing Ltd. This book was released on 2017-07-31 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Natural Language Processing with Java and LingPipe Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1783284684
Total Pages : 485 pages
Book Rating : 4.7/5 (832 download)

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Book Synopsis Natural Language Processing with Java and LingPipe Cookbook by : Breck Baldwin

Download or read book Natural Language Processing with Java and LingPipe Cookbook written by Breck Baldwin and published by Packt Publishing Ltd. This book was released on 2014-11-28 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.

Introducing Neuro-linguistic Programming

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Publisher : HarperCollins UK
ISBN 13 : 1855383446
Total Pages : 276 pages
Book Rating : 4.8/5 (553 download)

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Book Synopsis Introducing Neuro-linguistic Programming by : Joseph O'Connor

Download or read book Introducing Neuro-linguistic Programming written by Joseph O'Connor and published by HarperCollins UK. This book was released on 2002 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some people appear more gifted than others. NLP, a growing development in applied psychology, describes what they do differently and explains these patterns of excellence.

The Natural Language Processing Workshop

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Publisher : Packt Publishing Ltd
ISBN 13 : 1800200803
Total Pages : 451 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis The Natural Language Processing Workshop by : Rohan Chopra

Download or read book The Natural Language Processing Workshop written by Rohan Chopra and published by Packt Publishing Ltd. This book was released on 2020-08-17 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Make NLP easy by building chatbots and models, and executing various NLP tasks to gain data-driven insights from raw text data Key FeaturesGet familiar with key natural language processing (NLP) concepts and terminologyExplore the functionalities and features of popular NLP toolsLearn how to use Python programming and third-party libraries to perform NLP tasksBook 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 learnObtain, verify, clean and transform text data into a correct format for useUse methods such as tokenization and stemming for text extractionDevelop a classifier to classify comments in Wikipedia articlesCollect data from open websites with the help of web scrapingTrain a model to detect topics in a set of documents using topic modelingDiscover techniques to represent text as word and document vectorsWho 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.

Natural Language Processing Fundamentals

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Publisher : Packt Publishing Ltd
ISBN 13 : 178995598X
Total Pages : 374 pages
Book Rating : 4.7/5 (899 download)

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Book Synopsis Natural Language Processing Fundamentals by : Sohom Ghosh

Download or read book Natural Language Processing Fundamentals written by Sohom Ghosh and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key FeaturesAssimilate key NLP concepts and terminologies Explore popular NLP tools and techniquesGain practical experience using NLP in application codeBook 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 learnObtain, verify, and clean data before transforming it into a correct format for usePerform data analysis and machine learning tasks using PythonUnderstand the basics of computational linguisticsBuild models for general natural language processing tasksEvaluate the performance of a model with the right metricsVisualize, quantify, and perform exploratory analysis from any text dataWho 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.

Java Deep Learning Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1788999479
Total Pages : 294 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Java Deep Learning Cookbook by : Rahul Raj

Download or read book Java Deep Learning Cookbook written by Rahul Raj and published by Packt Publishing Ltd. This book was released on 2019-11-08 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch Key FeaturesInstall and configure Deeplearning4j to implement deep learning models from scratchExplore recipes for developing, training, and fine-tuning your neural network models in JavaModel neural networks using datasets containing images, text, and time-series dataBook Description Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently. This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results. By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java. What you will learnPerform data normalization and wrangling using DL4JBuild deep neural networks using DL4JImplement CNNs to solve image classification problemsTrain autoencoders to solve anomaly detection problems using DL4JPerform benchmarking and optimization to improve your model's performanceImplement reinforcement learning for real-world use cases using RL4JLeverage the capabilities of DL4J in distributed systemsWho this book is for If you are a data scientist, machine learning developer, or a deep learning enthusiast who wants to implement deep learning models in Java, this book is for you. Basic understanding of Java programming as well as some experience with machine learning and neural networks is required to get the most out of this book.

Keras Deep Learning Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1788623088
Total Pages : 244 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Keras Deep Learning Cookbook by : Rajdeep Dua

Download or read book Keras Deep Learning Cookbook written by Rajdeep Dua and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key FeaturesUnderstand different neural networks and their implementation using KerasExplore recipes for training and fine-tuning your neural network modelsPut your deep learning knowledge to practice with real-world use-cases, tips, and tricksBook Description Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learnInstall and configure Keras in TensorFlowMaster neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNsWork with various datasets and models used for image and text classificationDevelop text summarization and reinforcement learning models using KerasWho this book is for Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.