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

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...

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Bibliographic Details
Main Author: Beysolow II, Taweh (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2018.
Edition:1st ed. 2018.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

MARC

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505 0 |a 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. 
520 |a 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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