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Applied Natural Language Processing with Python

- Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing

Über Applied Natural Language Processing with Python

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 neednΓÇÖt feel that you need be an expert to understand the content.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9781484237328
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 150
  • Veröffentlicht:
  • 12. September 2018
  • Ausgabe:
  • 1
  • Abmessungen:
  • 157x234x9 mm.
  • Gewicht:
  • 276 g.
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Beschreibung von Applied Natural Language Processing with Python

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 neednΓÇÖt feel that you need be an expert to understand the content.

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