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

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Taweh Beysolow II

Applied Natural Language Processing with Python

Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

Taweh Beysolow II

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English

APress
12 September 2018

Program concepts & learning to program; Programming & scripting languages: general; Databases

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.

By: Taweh Beysolow II
Imprint: APress
Country of Publication: United States
Edition: 1st ed.
Dimensions: Height: 235mm, Width: 155mm,
Weight: 454g
ISBN: 9781484237328
ISBN 10: 1484237323
Pages: 150
Publication Date: 12 September 2018
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Taweh Beysolow II is a Machine Learning Scientist and Author currently based in the United States. He has a Bachelor of Science degree in Economics from St. Johns University and a Master of Science in Applied Statistics from Fordham University. His professional experience has included applying machine learning and natural language processing techniques to financial, text (structured and unstructured), and social media data.