Natural Language Processing With Spark Nlp

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Natural Language Processing with Spark NLP

Alex Thomas
Natural Language Processing with Spark NLP Book PDF

Author : Alex Thomas
Publisher : O'Reilly Media
Page : 367 pages
File Size : 40,8 Mb
Release : 2020-06-25
Category : Computers
ISBN : 9781492047735

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Natural Language Processing with Spark NLP by Alex Thomas Pdf

If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

Natural Language Processing with Spark NLP

Alex Thomas
Natural Language Processing with Spark NLP Book PDF

Author : Alex Thomas
Publisher : "O'Reilly Media, Inc."
Page : 411 pages
File Size : 48,8 Mb
Release : 2020-06-25
Category : Computers
ISBN : 9781492047711

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Natural Language Processing with Spark NLP by Alex Thomas Pdf

If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

Natural Language Processing with Spark NLP

Alex Thomas
Natural Language Processing with Spark NLP Book PDF

Author : Alex Thomas
Publisher : Unknown
Page : 37 pages
File Size : 53,8 Mb
Release : 2020
Category : Electronic
ISBN : 1492047759

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Natural Language Processing with Spark NLP by Alex Thomas Pdf

If you want to build an enterprise-quality application that uses natural language text, but aren't sure where to begin or what tools to use, this practical guide will help get you started. You'll explore special concerns for developing text-based applications, such as performance. Alex Thomas, data scientist at Indeed, shows software engineers and data scientists how to build scalable NLP applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from NLP basics to applications of powerful modern techniques. Process text in a distributed environment using Spark NLP, a production-ready library for NLP built on Spark Create, tune, and deploy your own word embeddings Adapt your NLP applications to multiple languages Use text in machine learning and deep learning Learn why these techniques work from a machine learning, linguistic, and practical point of view.

Next-Generation Machine Learning with Spark

Butch Quinto
Next Generation Machine Learning with Spark Book PDF

Author : Butch Quinto
Publisher : Apress
Page : 367 pages
File Size : 49,8 Mb
Release : 2020-02-22
Category : Computers
ISBN : 9781484256695

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Next-Generation Machine Learning with Spark by Butch Quinto Pdf

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.xAchieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM librariesDetect anomalies with the Isolation Forest algorithm for SparkUse the Spark NLP and Stanford CoreNLP libraries that support multiple languagesOptimize your ML workload with the Alluxio in-memory data accelerator for SparkUse GraphX and GraphFrames for Graph AnalysisPerform image recognition using convolutional neural networksUtilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.

Natural Language Processing with Python

Steven Bird,Ewan Klein,Edward Loper
Natural Language Processing with Python Book PDF

Author : Steven Bird,Ewan Klein,Edward Loper
Publisher : "O'Reilly Media, Inc."
Page : 506 pages
File Size : 55,5 Mb
Release : 2009-06-12
Category : Computers
ISBN : 9780596555719

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Natural Language Processing with Python by Steven Bird,Ewan Klein,Edward Loper Pdf

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 Processing with PyTorch

Delip Rao,Brian McMahan
Natural Language Processing with PyTorch Book PDF

Author : Delip Rao,Brian McMahan
Publisher : O'Reilly Media
Page : 256 pages
File Size : 46,7 Mb
Release : 2019-01-22
Category : Computers
ISBN : 9781491978207

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Natural Language Processing with PyTorch by Delip Rao,Brian McMahan Pdf

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

Practical Natural Language Processing

Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Practical Natural Language Processing Book PDF

Author : Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Publisher : O'Reilly Media
Page : 455 pages
File Size : 43,6 Mb
Release : 2020-06-17
Category : Computers
ISBN : 9781492054023

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Practical Natural Language Processing by Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana Pdf

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

Python Natural Language Processing

Jalaj Thanaki
Python Natural Language Processing Book PDF

Author : Jalaj Thanaki
Publisher : Packt Publishing Ltd
Page : 486 pages
File Size : 45,9 Mb
Release : 2017-07-31
Category : Computers
ISBN : 9781787285521

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Python Natural Language Processing by Jalaj Thanaki Pdf

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.

Applied Natural Language Processing in the Enterprise

Ankur A. Patel,Ajay Uppili Arasanipalai
Applied Natural Language Processing in the Enterprise Book PDF

Author : Ankur A. Patel,Ajay Uppili Arasanipalai
Publisher : "O'Reilly Media, Inc."
Page : 330 pages
File Size : 52,9 Mb
Release : 2021-05-12
Category : Computers
ISBN : 9781492062523

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Applied Natural Language Processing in the Enterprise by Ankur A. Patel,Ajay Uppili Arasanipalai Pdf

NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

Applied Natural Language Processing in the Enterprise

Ankur A. Patel,Ajay Uppili Arasanipalai
Applied Natural Language Processing in the Enterprise Book PDF

Author : Ankur A. Patel,Ajay Uppili Arasanipalai
Publisher : "O'Reilly Media, Inc."
Page : 336 pages
File Size : 40,5 Mb
Release : 2021-05-12
Category : Computers
ISBN : 9781492062547

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Applied Natural Language Processing in the Enterprise by Ankur A. Patel,Ajay Uppili Arasanipalai Pdf

NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

Natural Language Processing Fundamentals

Sohom Ghosh,Dwight Gunning
Natural Language Processing Fundamentals Book PDF

Author : Sohom Ghosh,Dwight Gunning
Publisher : Packt Publishing Ltd
Page : 374 pages
File Size : 48,7 Mb
Release : 2019-03-30
Category : Computers
ISBN : 9781789955989

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Natural Language Processing Fundamentals by Sohom Ghosh,Dwight Gunning Pdf

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.

Natural Language Processing with Python and spaCy

Yuli Vasiliev
Natural Language Processing with Python and spaCy Book PDF

Author : Yuli Vasiliev
Publisher : No Starch Press
Page : 217 pages
File Size : 46,7 Mb
Release : 2020-05-12
Category : Computers
ISBN : 9781718500525

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Natural Language Processing with Python and spaCy by Yuli Vasiliev Pdf

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.

Neural Networks for Natural Language Processing

S., Sumathi,M., Janani
Neural Networks for Natural Language Processing Book PDF

Author : S., Sumathi,M., Janani
Publisher : IGI Global
Page : 227 pages
File Size : 46,7 Mb
Release : 2019-11-29
Category : Computers
ISBN : 9781799811619

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Neural Networks for Natural Language Processing by S., Sumathi,M., Janani Pdf

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

Natural Language Processing

Yue Zhang,Zhiyang Teng
Natural Language Processing Book PDF

Author : Yue Zhang,Zhiyang Teng
Publisher : Cambridge University Press
Page : 487 pages
File Size : 53,6 Mb
Release : 2021-01-07
Category : Computers
ISBN : 9781108420211

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Natural Language Processing by Yue Zhang,Zhiyang Teng Pdf

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

Natural Language Processing Fundamentals for Developers

Oswald Campesato
Natural Language Processing Fundamentals for Developers Book PDF

Author : Oswald Campesato
Publisher : Mercury Learning and Information
Page : 520 pages
File Size : 42,5 Mb
Release : 2021-06-14
Category : Computers
ISBN : 9781683926559

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Natural Language Processing Fundamentals for Developers by Oswald Campesato Pdf

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