Practical natural language processing with python, Sri, Mathangi
Автор: Maosong Sun, Xiaojie Wang, Baobao Chang Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data ISBN: 3319690043 ISBN-13(EAN): 9783319690049 Издательство: Springer Рейтинг: Цена: 5300.00 р. Наличие на складе: Есть (3 шт.) Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.
Автор: Beysolow II Название: Applied Natural Language Processing with Python ISBN: 1484237323 ISBN-13(EAN): 9781484237328 Издательство: Springer Рейтинг: Цена: 7317.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1: What is Natural Language Processing? Chapter Goal: Establishing understanding of topic and give overview of textNo of pages: 10 pagesSub -Topics1. History of Natural Language Processing 2. Word Embeddings3. Neural Networks applied to Natural Language Processing 4. Python Packages Chapter 2: Review of Machine LearningChapter Goal: Discuss models that will be referenced in the textNo of pages: 30 pagesSub - Topics 1. Gradient Descent 2. Multi-Layer Perceptrons 3. Recurrent Neural Networks4. LSTM networks Chapter 3: Working with Raw Text Chapter Goal: Introduce reader to the fundamental aspects of Natural Language Processing that will be utilized more heavily in the chapters regarding No of pages: 30Sub - Topics: 1. Word Tokenization 2. Preprocessing and cleaning of text data3. Web crawling w/ SpaCy4. Lemmas, N-grams, and other NATURAL LANGUAGE PROCESSING concepts Chapter 4: Word Embeddings and their applicationChapter Goal: Introduce reader to the use cases for word embeddings and the packages we utilize for themNo of pages: 50 Sub - Topics: 1. Word2Vec2. Doc2Vec3. GloVe Chapter 5: Using Machine Learning w/ Natural language ProcessingChapter Goal: Give reader specific walkthroughs of advanced applications of Natural Language Processing using Machine Learning within greater applications (spellcheck and sentiment analysis)No of pages: 501. Tensorflow2. Keras3. Caffe
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP.
You'll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well.
Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques.
There is also a chapter dedicated to semantic analysis where you'll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release.
What You'll Learn -Understand NLP and text syntax, semantics and structure-Discover text cleaning and feature engineering-Review text classification and text clustering - Assess text summarization and topic models- Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Описание: This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples
Описание: This volume reports on excavations in advance of the development of a site in Norton-on-Derwent, North Yorkshire close to the line of the main Roman road running from the crossing point of the River Derwent near Malton Roman fort to York. This site provided much additional information on aspects of the poorly understood `small town` of Delgovicia.
Описание: Leverage your natural language processing skills to make sense of text. With this book, you`ll learn fundamental and advanced NLP techniques in Python that will help you to make your data fit for application in a wide variety of industries. You`ll also find recipes for overcoming common challenges in implementing NLP pipelines.
Описание: Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. The numbers of human-computer interaction instances are increasing so it`s becoming imperative that computers comprehend all major natural languages. Python`s powerful tools and libraries are evolved so much.
Автор: Kasliwal Nirant Название: Natural Language Processing with Python Quick Start Guide ISBN: 1789130387 ISBN-13(EAN): 9781789130386 Издательство: Неизвестно Рейтинг: Цена: 6435.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: NLP in Python is among the most sought-after skills among data scientists. With code and relevant case studies, this book will show how you can use industry grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.
Автор: Arumugam Rajesh, Shanmugmani Rajalingappaa Название: Hands-on Natural Language Processing with Python ISBN: 178913949X ISBN-13(EAN): 9781789139495 Издательство: Неизвестно Рейтинг: Цена: 8458.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. The book equips you with practical knowledge to implement deep learning in your linguistic applications using NLTk and Python`s popular deep learning library, TensorFlow.
Автор: Perkins Jacob, Hardeniya Nitin, Chopra Deepti Название: Natural Language Processing: Python and NLTK ISBN: 1787285103 ISBN-13(EAN): 9781787285101 Издательство: Неизвестно Рейтинг: Цена: 15631.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
