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|a Thomas, Alex
|c (Data scientist),
|e author.
|9 51553
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1 |
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|a Natural language processing with Spark NLP :
|b learning to understand text at Scale /
|c Alex Thomas.
|
| 250 |
|
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|a First edition.
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| 264 |
|
1 |
|a Sebastopol, CA :
|b O'Reilly Media,
|c c2020.
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| 264 |
|
4 |
|c ©2020
|
| 300 |
|
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|a xv, 347 pages :
|b illustrations ;
|c 24 cm.
|
| 500 |
|
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|a Includes index.
|
| 505 |
0 |
|
|a Part 1. Basics. Getting started -- Natural language basics -- NLP on Apache Spark -- Deep learning basics -- Part 2. Building blocks. Processing words -- Information retrieval -- Classification and regression -- Sequence modeling with Keras -- Information extraction -- Topic modeling -- Word embeddings -- Part 3. Applicasions. Sentiment analysis and emotion detection -- Building knowledge bases -- Search engine -- Chatbot -- Object character recognition -- Part 4. Building NLP systems. Supporting multiple languages -- Human labeling -- Productionizing NLP applications.
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| 520 |
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|a 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, pratical and theoretical explanations, and hads-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basics linguistics and writing systems to sentiment analysis and search engines. You'll also explore special concerns for developging text-based applications, such as performance.--
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|a Natural language processing (Computer science)
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|a Application software
|x Development.
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|a Text data mining.
|9 51557
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|a Computer science.
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