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Applied Natural Language Processing ...
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Beysolow II, Taweh.
Applied Natural Language Processing with Python = Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Applied Natural Language Processing with Python / by Taweh Beysolow II.
Reminder of title:
Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /
Author:
Beysolow II, Taweh.
Description:
XV, 150 p. 32 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Artificial intelligence. -
Online resource:
https://doi.org/10.1007/978-1-4842-3733-5
ISBN:
9781484237335
Applied Natural Language Processing with Python = Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /
Beysolow II, Taweh.
Applied Natural Language Processing with Python
Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /[electronic resource] :by Taweh Beysolow II. - 1st ed. 2018. - XV, 150 p. 32 illus.online resource.
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 .
ISBN: 9781484237335
Standard No.: 10.1007/978-1-4842-3733-5doiSubjects--Topical Terms:
559380
Artificial intelligence.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Applied Natural Language Processing with Python = Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /
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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.
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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. 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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