Taweh Beysolow

Applied Natural Language Processing with Python

Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

• Broschiertes Buch

Produktbeschreibung

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 abeginner 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.

Produktdetails

• Verlag: Apress / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4842-3732-8
• 1st ed.
• Seitenzahl: 168
• Erscheinungstermin: 12. September 2018
• Englisch
• Abmessung: 235mm x 155mm x 10mm
• Gewicht: 266g
• ISBN-13: 9781484237328
• ISBN-10: 1484237323
• Artikelnr.: 52487674

Autorenporträt

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.

Inhaltsangabe

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.