Applied Natural Language Processing with Python
Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing
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Beschreibung
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
Covers NLP packages such as NLTK, gensim,and SpaCy Approaches topics such as "topic modeling" and "text summarization" in a beginner-friendly manner Explains how to ingest text data via web crawlers for use in deep learning NLP algorithms such as Word2Vec and Doc2Vec
Autor*in
Taweh Beysolow II
Themen in »Applied Natural Language Processing with Python«
Natural Language Processing Machine Learning Deep Learning Python TensorFlow Keras Caffee Neural Networks