Applied Natural Language Processing In The Enterprise

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Applied Natural Language Processing in the Enterprise

Author : Ankur A. Patel
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062545
Total Pages : 336 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Applied Natural Language Processing in the Enterprise by : Ankur A. Patel

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Ankur A. Patel
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062529
Total Pages : 330 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Applied Natural Language Processing in the Enterprise by : Ankur A. Patel

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Practical Natural Language Processing

Author : Sowmya Vajjala
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

Applied Natural Language Processing in the Enterprise

Author : Ankur A Patel
Publisher :
ISBN 13 : 9781492062578
Total Pages : 350 pages
Book Rating : 4.0/5 (625 download)

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Book Synopsis Applied Natural Language Processing in the Enterprise by : Ankur A Patel

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A Patel and published by . This book was released on 2021-04-13 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly. If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory. Understand how state-of-the-art NLP models work Learn the tools of the trade, including frameworks popular today Perform NLP tasks such as text classification, semantic search, and reading comprehension Solve problems using new models like transformers and techniques such as transfer learning Build NLP models from scratch with performance comparable or superior to out-of-the-box systems Deploy your models to production and maintain their performance Implement a suite of NLP algorithms using Python and PyTorch

Natural Language Processing with Python

Author : Steven Bird
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.

Applied Natural Language Processing

Author : Steven P. Shwartz
Publisher :
ISBN 13 :
Total Pages : 328 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applied Natural Language Processing by : Steven P. Shwartz

Download or read book Applied Natural Language Processing written by Steven P. Shwartz and published by . This book was released on 1987 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides insight into the relationship between natural language processing and the use of artificial intelligence in the commercial world. Includes applications examples.

Natural Language Processing with TensorFlow

Author : Thushan Ganegedara
Publisher : Packt Publishing Ltd
ISBN 13 : 1788477758
Total Pages : 472 pages
Book Rating : 4.7/5 (884 download)

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Book Synopsis Natural Language Processing with TensorFlow by : Thushan Ganegedara

Download or read book Natural Language Processing with TensorFlow written by Thushan Ganegedara and published by Packt Publishing Ltd. This book was released on 2018-05-31 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful.

Natural Language Processing with Transformers, Revised Edition

Author : Lewis Tunstall
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 PyTorch

Author : Delip Rao
Publisher : O'Reilly Media
ISBN 13 : 1491978201
Total Pages : 256 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Natural Language Processing with PyTorch by : Delip Rao

Download or read book Natural Language Processing with PyTorch written by Delip Rao and published by O'Reilly Media. This book was released on 2019-01-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Natural Language Processing with Spark NLP

Author : Alex Thomas
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492047716
Total Pages : 411 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Natural Language Processing with Spark NLP by : Alex Thomas

Download or read book Natural Language Processing with Spark NLP written by Alex Thomas and published by "O'Reilly Media, Inc.". This book was released on 2020-06-25 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and Text Mining

Author : Anne Kao
Publisher : Springer Science & Business Media
ISBN 13 : 1846287545
Total Pages : 272 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Natural Language Processing and Text Mining by : Anne Kao

Download or read book Natural Language Processing and Text Mining written by Anne Kao and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.

Applied Natural Language Processing with Python

Author : Taweh Beysolow II
Publisher : Apress
ISBN 13 : 9781484237328
Total Pages : 150 pages
Book Rating : 4.2/5 (373 download)

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Book Synopsis Applied Natural Language Processing with Python by : Taweh Beysolow II

Download or read book Applied Natural Language Processing with Python written by Taweh Beysolow II and published by Apress. This book was released on 2018-09-12 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment. What You Will Learn Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim Manipulate and preprocess raw text data in formats such as .txt and .pdf Strengthen your skills in data science by learning both the theory and the application of various algorithms Who This Book Is For You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content.

Natural Language Processing with SAS

Author :
Publisher :
ISBN 13 : 9781952363184
Total Pages : 74 pages
Book Rating : 4.3/5 (631 download)

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Book Synopsis Natural Language Processing with SAS by :

Download or read book Natural Language Processing with SAS written by and published by . This book was released on 2020-08-31 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and emulate written or spoken human language. NLP draws from many disciplines including human-generated linguistic rules, machine learning, and deep learning to fill the gap between human communication and machine understanding. The papers included in this special collection demonstrate how NLP can be used to scale the human act of reading, organizing, and quantifying text data.

Natural Language Processing with AWS AI Services

Author : Mona M
Publisher : Packt Publishing Ltd
ISBN 13 : 1801815488
Total Pages : 508 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Natural Language Processing with AWS AI Services by : Mona M

Download or read book Natural Language Processing with AWS AI Services written by Mona M and published by Packt Publishing Ltd. This book was released on 2021-11-26 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work through interesting real-life business use cases to uncover valuable insights from unstructured text using AWS AI services Key FeaturesGet to grips with AWS AI services for NLP and find out how to use them to gain strategic insightsRun Python code to use Amazon Textract and Amazon Comprehend to accelerate business outcomesUnderstand how you can integrate human-in-the-loop for custom NLP use cases with Amazon A2IBook Description Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production. To start with, you'll understand the importance of NLP in today's business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic. Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications. What you will learnAutomate various NLP workflows on AWS to accelerate business outcomesUse Amazon Textract for text, tables, and handwriting recognition from images and PDF filesGain insights from unstructured text in the form of sentiment analysis, topic modeling, and more using Amazon ComprehendSet up end-to-end document processing pipelines to understand the role of humans in the loopDevelop NLP-based intelligent search solutions with just a few lines of codeCreate both real-time and batch document processing pipelines using PythonWho this book is for If you're an NLP developer or data scientist looking to get started with AWS AI services to implement various NLP scenarios quickly, this book is for you. It will show you how easy it is to integrate AI in applications with just a few lines of code. A basic understanding of machine learning (ML) concepts is necessary to understand the concepts covered. Experience with Jupyter notebooks and Python will be helpful.

Natural Language Processing for Online Applications

Author : Peter Jackson
Publisher : John Benjamins Publishing
ISBN 13 : 9027292442
Total Pages : 243 pages
Book Rating : 4.0/5 (272 download)

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Book Synopsis Natural Language Processing for Online Applications by : Peter Jackson

Download or read book Natural Language Processing for Online Applications written by Peter Jackson and published by John Benjamins Publishing. This book was released on 2007-06-05 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.

Transformers for Natural Language Processing

Author : Denis Rothman
Publisher : Packt Publishing Ltd
ISBN 13 : 1800568630
Total Pages : 385 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Transformers for Natural Language Processing by : Denis Rothman

Download or read book Transformers for Natural Language Processing written by Denis Rothman and published by Packt Publishing Ltd. This book was released on 2021-01-29 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as casual language analysis and computer vision tasks, as well as an introduction to OpenAI's Codex. Key FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machineTest transformer models on advanced use casesBook Description The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What you will learnUse the latest pretrained transformer modelsGrasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer modelsCreate language understanding Python programs using concepts that outperform classical deep learning modelsUse a variety of NLP platforms, including Hugging Face, Trax, and AllenNLPApply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and moreMeasure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is for Since the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include experienced deep learning & NLP practitioners and data analysts & data scientists who want to process the increasing amounts of language-driven data.

Natural Language Processing Fundamentals

Author : Sohom Ghosh
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.