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Natural Language - Paperback, by Srinivasa-Desikan Bhargav - Very Good

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Item specifics

Condition
Very Good: A book that does not look new and has been read but is in excellent condition. No obvious ...
Book Title
Natural Language Processing and Computational Linguistics: A prac
ISBN
9781788838535
Publication Year
2018
Type
Textbook
Format
Trade Paperback
Language
English
Publication Name
Natural Language Processing and Computational Linguistics : A Practical Guide to Text Analysis with Python, Gensim, SpaCy, and Keras
Author
Bhargav Srinivasa-Desikan
Item Length
3.6in
Publisher
Packt Publishing, The Limited
Item Width
3in
Number of Pages
306 Pages

About this product

Product Information

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!

Product Identifiers

Publisher
Packt Publishing, The Limited
ISBN-10
178883853x
ISBN-13
9781788838535
eBay Product ID (ePID)
15038585097

Product Key Features

Author
Bhargav Srinivasa-Desikan
Publication Name
Natural Language Processing and Computational Linguistics : A Practical Guide to Text Analysis with Python, Gensim, SpaCy, and Keras
Format
Trade Paperback
Language
English
Publication Year
2018
Type
Textbook
Number of Pages
306 Pages

Dimensions

Item Length
3.6in
Item Width
3in

Additional Product Features

Table of Content
Table of Contents What is Text Analysis? Python Tips for Text Analysis spaCy's Language Models Gensim - Vectorizing text and transformations and n-grams POS-Tagging and its Applications NER-Tagging and its Applications Dependency Parsing Top Models Advanced Topic Modelling Clustering and Classifying Text Similarity Queries and Summarization Word2Vec, Doc2Vec and Gensim Deep Learning for text Keras and spaCy for Deep Learning Sentiment Analysis and ChatBots
Target Audience
Trade
Topic
Natural Language Processing, Neural Networks, Intelligence (Ai) & Semantics
Genre
Computers

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