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Applied Natural Language Processing with Python : Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing / by Taweh Beysolow II.

By: Material type: TextTextPublication details: Apress 2021Edition: 1st ed. 2018Description: 1 online resource (XV, 150 pages 32 illustrations)ISBN:
  • 9781484237335
Subject(s): DDC classification:
  • 006.3 23 BEY
Contents:
Chapter 1: What is Natural Language Processing? -- Chapter 2: Review of Machine Learning -- Chapter 3: Working with Raw Text -- Chapter 4: Word Embeddings and their application -- Chapter 5: Using Machine Learning with Natural Language Processing.
Summary: 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. You will: 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 .
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Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Computer Science Dept. of Computer Science 006.3 BEY (Browse shelf(Opens below)) Available DCS5049

Chapter 1: What is Natural Language Processing? -- Chapter 2: Review of Machine Learning -- Chapter 3: Working with Raw Text -- Chapter 4: Word Embeddings and their application -- Chapter 5: Using Machine Learning with Natural Language Processing.

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. You will: 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 .

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