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Applied Natural Language Processing with Python : Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

By: (Author) Taweh Beysolow II

Extended Catalogue

Ksh 9,900.00

Format: Paperback / Softback

ISBN-10: 1484237323

ISBN-13: 9781484237328

Publisher: APress

Imprint: APress

Country of Manufacture: US

Country of Publication: GB

Publication Date: Sep 12th, 2018

Print length: 150 Pages

Weight: 276 grams

Dimensions (height x width x thickness): 23.40 x 15.70 x 0.90 cms

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  • Description

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Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment. What You Will Learn  Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and GensimManipulate and preprocess raw text data in formats such as .txt and .pdfStrengthen your skills in data science by learning both the theory and the application of various algorithms  Who This Book Is For You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content.
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. 

Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment.


What You Will Learn  
  • Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim
  • Manipulate and preprocess raw text data in formats such as .txt and .pdf
  • Strengthen your skills in data science by learning both the theory and the application of various algorithms  

Who This Book Is For 

You should be at least a beginner in ML to get the most out of this text, but you needn''t feel that you need be an expert to understand the content.


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