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- Author: Taweh Beysolow Ii
- Publisher: Apress
- ISBN-10: 1484237323
- ISBN-13: 9781484237328
- Format: 15.6 x 23.4 x 0.9 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Applied Natural Language Processing with Python (e-book) (used book) | bookbook.eu
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Description
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.
- 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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 15d.17:01:57
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Taweh Beysolow Ii
- Publisher: Apress
- ISBN-10: 1484237323
- ISBN-13: 9781484237328
- Format: 15.6 x 23.4 x 0.9 cm, softcover
- Language: English English
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.
- 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.
Reviews