Introduction To Machine Learning And Natural Language Processing
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Introduction To Machine Learning And Natural Language Processing
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Author : Dr.T.Saroja
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-11-21
Introduction To Machine Learning And Natural Language Processing written by Dr.T.Saroja and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-21 with Computers categories.
Dr.T.Saroja, Assistant Professor, Department of Software Applications, Agurchand Manmull Jain College, Chennai, Tamil Nadu, India. Dr.S.Sasikala, Assistant Professor, Department of Computer Science, Agurchand Manmull Jain College, Chennai, Tamil Nadu, India.
Introduction To Machine Learning And Natural Language Processing
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Author : Mrs.Chinni Bala Vijaya Durga
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-10-22
Introduction To Machine Learning And Natural Language Processing written by Mrs.Chinni Bala Vijaya Durga and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.
Mrs.Chinni Bala Vijaya Durga, Associate Professor, Department of Computer Science & Engineering [AI & ML], PSCMR College of Engineering and Technology, Vijayawada, Andhra Pradesh, India. Dr.J.Naga Madhuri, Assistant Professor, Department of English, Velagapudi Rama Krishna Siddhartha Engineering College (Deemed to be University), Vijayawada, Andhra Pradesh, India.
Introduction To Machine Learning And Natural Language Processing
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Author : Dr.Ravi Kumar Saidala
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-07-19
Introduction To Machine Learning And Natural Language Processing written by Dr.Ravi Kumar Saidala and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-19 with Computers categories.
Dr.Ravi Kumar Saidala, Associate Professor, Department of CSE – Data Science, CMR University, Bangalore, Karnataka, India. Mr.Satyanarayanareddy Marri, Assistant Professor, Department of Artificial Intelligence, Anurag University, Hyderabad, Telangana, India. Dr.D.Usha Rani, Associate Professor, Department of Computer Science and Applications, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India. Prof.U.Ananthanagu, Assistant Professor, Department of CSE, Alliance University, Bangalore, Karnataka, India.
Introduction To Machine Learning And Natural Language Processing
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Author : Dr.Kongara Srinivasa Rao
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-06-27
Introduction To Machine Learning And Natural Language Processing written by Dr.Kongara Srinivasa Rao and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-27 with Computers categories.
Dr.Kongara Srinivasa Rao, Assistant Professor, Department of Computer Science and Engineering, Faculty of Science and Technology (ICFAI Tech), ICFAI Foundation for Higher Education (IFHE), Hyderabad, Telangana, India. Dr.K.Sreeramamurthy, Professor, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, Telangana, India. Dr.Yaswanth Kumar Alapati, Associate Professor, Department of Information Technology, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India.
Comprehensive Guide To Machine Learning Deep Learning And Natural Language Processing
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Author : Dr.D.Veena Raja
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-01-17
Comprehensive Guide To Machine Learning Deep Learning And Natural Language Processing written by Dr.D.Veena Raja and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with Computers categories.
Dr.D.Veena Raja, Assistant Professor, Department of Artificial Intelligence and Data Science, DMI College of Engineering, Chennai, Tamil Nadu, India. Dr.S.Ponmaniraj, Professor, Department of Computational Intelligence, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Tamil Nadu, India. A.Divya, Assistant Professor, Department of Artificial Intelligence and Data Science, DMI College of Engineering, Chennai, Tamil Nadu, India. Dr.L.Jimson, Assistant Professor, Department of Artificial Intelligence and Machine Learning, DMI College of Engineering, Chennai, Tamil Nadu, India. Dr.K.Kalai Kumar, Associate Professor, Department of Artificial Intelligence and Data Science, DMI College of Engineering, Chennai, Tamil Nadu, India.
Natural Language Processing Crash Course For Beginners
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Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-08-04
Natural Language Processing Crash Course For Beginners written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with categories.
Natural Language Processing Crash Course for Beginners Artificial Intelligence (AI) isn't the latest fad! The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings. How Is This Book Different? This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder. The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning. Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing? Environment Setup and Python Crash Course Introduction to Deep Learning Text Cleaning and Manipulation Common NLP Tasks Importing Text Data from Various Sources Word Embeddings: Converting Words to Numbers IMDB Movies Sentimental Analysis Ham and Spam Message Classification Text Summarization and Topic Modeling Text Classification with Deep Learning Text Translation Using Seq2Seq Model State of the Art NLP with BERT Transformers Hands-on NLP Projects/Articles for Practice Exercise Solutions Click the BUY button and download the book now to start your Natural Language Processing journey.
Deep Learning For Natural Language Processing
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Author : Mihai Surdeanu
language : en
Publisher: Cambridge University Press
Release Date : 2024-02-08
Deep Learning For Natural Language Processing written by Mihai Surdeanu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-08 with Computers categories.
Provides a clear, accessible introduction to deep learning for natural language processing, covering both practical and theoretical aspects.
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
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.
Introduction To Natural Language Processing
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Author : Xiaochun Cheng
language : en
Publisher: CRC Press
Release Date : 2025-06-27
Introduction To Natural Language Processing written by Xiaochun Cheng and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Computers categories.
This book provides a thorough and comprehensive introduction to natural language processing (NLP), a critical field at the intersection of artificial intelligence and computational linguistics. It explores key techniques such as sentiment analysis, which enables the detection of emotional tone in text, machine translation, facilitating the conversion of text between languages, and named entity recognition (NER), which identifies and classifies entities like names, dates, and locations within text data. The book delves into deep learning advancements, particularly the use of neural networks such as transformers and recurrent models, which have revolutionized NLP applications. Readers will gain insights into how these models drive innovations in areas such as text classification, language generation, and speech recognition. In addition to technical concepts, the book also addresses the ethical considerations surrounding NLP, emphasizing the responsible use of AI technologies to mitigate issues like bias, misinformation, and privacy concerns. Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service. This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.