Mastering Natural Language Processing
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Mastering Natural Language Processing With Python
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Author : Deepti Chopra
language : en
Publisher: Packt Publishing
Release Date : 2016-06-10
Mastering Natural Language Processing With Python written by Deepti Chopra and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-10 with Computers categories.
Maximize your NLP capabilities while creating amazing NLP projects in PythonAbout This Book* Learn to implement various NLP tasks in Python* Gain insights into the current and budding research topics of NLP* This is a comprehensive step-by-step guide to help students and researchers create their own projects based on real-life applicationsWho This Book Is ForThis book is for intermediate level developers in NLP with a reasonable knowledge level and understanding of Python.What You Will Learn* Implement string matching algorithms and normalization techniques* Implement statistical language modeling techniques* Get an insight into developing a stemmer, lemmatizer, morphological analyzer, and morphological generator* Develop a search engine and implement POS tagging concepts and statistical modeling concepts involving the n gram approach* Familiarize yourself with concepts such as the Treebank construct, CFG construction, the CYK Chart Parsing algorithm, and the Earley Chart Parsing algorithm* Develop an NER-based system and understand and apply the concepts of sentiment analysis* Understand and implement the concepts of Information Retrieval and text summarization* Develop a Discourse Analysis System and Anaphora Resolution based systemIn DetailNatural Language Processing is one of the fields of computational linguistics and artificial intelligence that is concerned 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.This book will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK.You will sequentially be guided through applying machine learning tools to develop various models. We'll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Sentiment Analysis, Text Summarization, and Anaphora Resolution.
Mastering Natural Language Processing With Python
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Author : Nisheeth Joshi
language : en
Publisher:
Release Date : 2018
Mastering Natural Language Processing With Python written by Nisheeth Joshi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"Natural Language Processing is one of the fields of computational linguistics and artificial intelligence that is concerned 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.This course will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK. You will sequentially be guided through applying machine learning tools to develop various models. We'll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Text Summarization, and Anaphora Resolution."--Resource description page.
Mastering Natural Language Processing
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Author : Cybellium Ltd
language : en
Publisher: Cybellium Ltd
Release Date :
Mastering Natural Language Processing written by Cybellium Ltd and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unveil the Secrets of Language Understanding and Generation In the realm of artificial intelligence and communication, Natural Language Processing (NLP) stands as a transformative force that bridges the gap between humans and machines. "Mastering Natural Language Processing" is your definitive guide to comprehending and harnessing the potential of this dynamic field, empowering you to create intelligent language-based applications with precision. About the Book: As technology evolves, the ability to understand and generate human language becomes increasingly essential. "Mastering Natural Language Processing" offers a comprehensive exploration of NLP—a crucial discipline in the world of AI and communication. This book caters to both beginners and experienced learners aiming to excel in NLP concepts, techniques, and applications. Key Features: NLP Fundamentals: Begin by understanding the core principles of Natural Language Processing. Learn about linguistic concepts, tokenization, and language models. Text Classification and Sentiment Analysis: Dive into text analysis techniques. Explore methods for classifying text and determining sentiment, enabling you to understand user opinions and emotions. Named Entity Recognition: Grasp the art of identifying entities in text. Understand how to extract names, places, dates, and other crucial information from unstructured data. Language Generation: Explore techniques for generating human-like language. Learn how to create chatbots, language models, and automated content. Machine Translation: Understand the significance of machine translation. Learn how to build systems that translate text between languages with accuracy. Speech Recognition: Delve into the realm of speech recognition. Explore techniques for converting spoken language into text, enabling voice interfaces and transcription. Question Answering Systems: Grasp the power of question-answering systems. Learn how to build applications that provide answers to user questions based on available data. Real-World Applications: Gain insights into how NLP is applied across industries. From customer service to healthcare, discover the diverse applications of natural language processing. Why This Book Matters: In an age of communication and interaction, mastering NLP offers a competitive advantage. "Mastering Natural Language Processing" empowers data scientists, developers, and technology enthusiasts to leverage NLP concepts, enabling them to create intelligent language-based applications that enhance user experiences and drive innovation. Revolutionize Communication with AI: In the landscape of artificial intelligence, Natural Language Processing is transforming how humans and machines interact. "Mastering Natural Language Processing" equips you with the knowledge needed to leverage NLP concepts, enabling you to create intelligent language-based applications that bridge communication gaps and redefine possibilities. Whether you're a seasoned practitioner or new to the world of NLP, this book will guide you in building a solid foundation for effective language-based solutions. Your journey to mastering Natural Language Processing starts here. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Mastering Transformers
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Author : Savaş Yıldırım
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-15
Mastering Transformers written by Savaş Yıldırım and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-15 with Computers categories.
Take a problem-solving approach to learning all about transformers and get up and running in no time by implementing methodologies that will build the future of NLP Key Features Explore quick prototyping with up-to-date Python libraries to create effective solutions to industrial problems Solve advanced NLP problems such as named-entity recognition, information extraction, language generation, and conversational AI Monitor your model's performance with the help of BertViz, exBERT, and TensorBoard Book DescriptionTransformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, you'll learn how to build various transformer-based NLP applications using the Python Transformers library. The book gives you an introduction to Transformers by showing you how to write your first hello-world program. You'll then learn how a tokenizer works and how to train your own tokenizer. As you advance, you'll explore the architecture of autoencoding models, such as BERT, and autoregressive models, such as GPT. You'll see how to train and fine-tune models for a variety of natural language understanding (NLU) and natural language generation (NLG) problems, including text classification, token classification, and text representation. This book also helps you to learn efficient models for challenging problems, such as long-context NLP tasks with limited computational capacity. You'll also work with multilingual and cross-lingual problems, optimize models by monitoring their performance, and discover how to deconstruct these models for interpretability and explainability. Finally, you'll be able to deploy your transformer models in a production environment. By the end of this NLP book, you'll have learned how to use Transformers to solve advanced NLP problems using advanced models.What you will learn Explore state-of-the-art NLP solutions with the Transformers library Train a language model in any language with any transformer architecture Fine-tune a pre-trained language model to perform several downstream tasks Select the right framework for the training, evaluation, and production of an end-to-end solution Get hands-on experience in using TensorBoard and Weights & Biases Visualize the internal representation of transformer models for interpretability Who this book is for This book is for deep learning researchers, hands-on NLP practitioners, as well as ML/NLP educators and students who want to start their journey with Transformers. Beginner-level machine learning knowledge and a good command of Python will help you get the best out of this book.
Mastering Natural Language Processing
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Author : Ravindra Kumar Nayak
language : en
Publisher: Independently Published
Release Date : 2024-01-05
Mastering Natural Language Processing written by Ravindra Kumar Nayak and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-05 with Computers categories.
"Unveiling NLP" is a comprehensive guide that navigates readers through the intricate landscape of Natural Language Processing (NLP). Covering fundamental concepts like tokenization and sentiment analysis, the book progresses to advanced topics, including model building, evaluation, and deployment. With hands-on projects, it demystifies NLP, making it accessible to both technical and non-technical readers. The journey concludes with a comparative analysis, empowering readers to choose the most effective models. Whether delving into text clustering or role-based classification, this book transforms NLP from a complex subject into a piece of cake, fostering a deeper understanding and appreciation for language processing intricacies.
Mastering Nlp From Foundations To Llms
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Author : Lior Gazit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-26
Mastering Nlp From Foundations To Llms written by Lior Gazit and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-26 with Computers categories.
Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key Features Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT Master embedding techniques and machine learning principles for real-world applications Understand the mathematical foundations of NLP and deep learning designs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learn Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python Model and classify text using traditional machine learning and deep learning methods Understand the theory and design of LLMs and their implementation for various applications in AI Explore NLP insights, trends, and expert opinions on its future direction and potential Who this book is for This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.
Natural Language Processing Python And Nltk
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Author : Nitin Hardeniya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-11-22
Natural Language Processing Python And Nltk written by Nitin Hardeniya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-22 with Computers categories.
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.
Introduction To Natural Language Processing
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Author : Jacob Eisenstein
language : en
Publisher: MIT Press
Release Date : 2019-10-01
Introduction To Natural Language Processing written by Jacob Eisenstein and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-01 with Computers categories.
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
The Language Of Machines
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Author : Morgan David Sheldon
language : en
Publisher: Sheldon Morgan David
Release Date : 2024-03-30
The Language Of Machines written by Morgan David Sheldon and has been published by Sheldon Morgan David this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-30 with Computers categories.
The Language of Machines: Mastering Natural Language Processing Algorithms, written by Dr. Sophia Jennings, offers a comprehensive guide to understanding and communicating with machines in the age of advanced technology. With a focus on Natural Language Processing (NLP), this book provides both beginners and experienced practitioners with valuable insights into the foundations, methodologies, and advanced techniques of NLP. Throughout the fourteen chapters, readers will gain a strong theoretical foundation in NLP. Dr. Jennings starts with an exploration of basic language structure and syntax, explaining the algorithms used in NLP and computational linguistics. The book then covers the various stages of NLP, including text preprocessing, morphological analysis, and part-of-speech tagging, with real-world examples and custom illustrations to enhance understanding. Moving on to core NLP tasks, The Language of Machines covers sentiment analysis, named entity recognition, topic modeling, and information extraction. Dr. Jennings presents classical methods and state-of-the-art advancements, giving readers a comprehensive perspective on the evolution of NLP. The book also offers practical implementation through hands-on coding exercises that demonstrate the power of NLP algorithms, allowing readers to replicate real-world scenarios. Additionally, Dr. Jennings addresses the importance of evaluating and measuring the performance of NLP models. The book explores metrics and evaluation techniques and provides an overview of NLP evaluation frameworks. Readers will gain insights into overcoming common challenges encountered in deploying NLP applications. The Language of Machines concludes with an exploration of emerging frontiers in NLP, including deep learning approaches, neural networks, and the integration of NLP with other branches of AI, such as computer vision. Dr. Jennings bridges theoretical concepts to real-world applications, enabling readers to understand the potential of NLP in shaping our AI-driven future. By the end of this enlightening journey, readers will have the skills to understand and construct NLP algorithms, effectively communicate with machines, and evaluate NLP models. The Language of Machines equips aspiring NLP practitioners with the essential tools to embark on their own transformative journey in the world of Natural Language Processing.
Mastering Spacy
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Author : Duygu Altinok
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-09
Mastering Spacy written by Duygu Altinok and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-09 with Computers categories.
Build end-to-end industrial-strength NLP models using advanced morphological and syntactic features in spaCy to create real-world applications with ease Key FeaturesGain an overview of what spaCy offers for natural language processingLearn details of spaCy's features and how to use them effectivelyWork through practical recipes using spaCyBook Description spaCy is an industrial-grade, efficient NLP Python library. It offers various pre-trained models and ready-to-use features. Mastering spaCy provides you with end-to-end coverage of spaCy's features and real-world applications. You'll begin by installing spaCy and downloading models, before progressing to spaCy's features and prototyping real-world NLP apps. Next, you'll get familiar with visualizing with spaCy's popular visualizer displaCy. The book also equips you with practical illustrations for pattern matching and helps you advance into the world of semantics with word vectors. Statistical information extraction methods are also explained in detail. Later, you'll cover an interactive business case study that shows you how to combine all spaCy features for creating a real-world NLP pipeline. You'll implement ML models such as sentiment analysis, intent recognition, and context resolution. The book further focuses on classification with popular frameworks such as TensorFlow's Keras API together with spaCy. You'll cover popular topics, including intent classification and sentiment analysis, and use them on popular datasets and interpret the classification results. By the end of this book, you'll be able to confidently use spaCy, including its linguistic features, word vectors, and classifiers, to create your own NLP apps. What you will learnInstall spaCy, get started easily, and write your first Python scriptUnderstand core linguistic operations of spaCyDiscover how to combine rule-based components with spaCy statistical modelsBecome well-versed with named entity and keyword extractionBuild your own ML pipelines using spaCyApply all the knowledge you've gained to design a chatbot using spaCyWho this book is for This book is for data scientists and machine learners who want to excel in NLP as well as NLP developers who want to master spaCy and build applications with it. Language and speech professionals who want to get hands-on with Python and spaCy and software developers who want to quickly prototype applications with spaCy will also find this book helpful. Beginner-level knowledge of the Python programming language is required to get the most out of this book. A beginner-level understanding of linguistics such as parsing, POS tags, and semantic similarity will also be useful.