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Blueprints for Text Analytics using Python : Machine Learning Based Solutions for Common Real World (NLP) Applications - Jens Albrecht

Blueprints for Text Analytics using Python

Machine Learning Based Solutions for Common Real World (NLP) Applications

By: Jens Albrecht, Sidharth Ramachandran, Christian Winkler

Paperback | 22 December 2020

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Turning text into valuable information is essential for many businesses looking to gain a competitive advantage.

There have many improvements in natural language processing and users have a lot of options when choosing to work on a problem. However, it's not always clear which NLP tools or libraries would work for a business use--or which techniques you should use and in what order.

This practical book provides theoretical background and real-world case studies with detailed code examples to help developers and data scientists obtain insight from text online.

Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler use blueprints for text-related problems that apply state-of-the-art machine learning methods in Python.

If you have a fundamental understanding of statistics and machine learning along with basic programming experience in Python, you're ready to get started.

You'll learn how to:
  • Crawl and clean then explore and visualize textual data in different formats
  • Preprocess and vectorize text for machine learning
  • Apply methods for classification, topic analysis, summarization, and knowledge extraction
  • Use semantic word embeddings and deep learning approaches for complex problems
  • Work with Python NLP libraries like spaCy, NLTK, and Gensim in combination with scikit-learn, Pandas, and PyTorch

You Can Find This Book In

Non-FictionComputing & I.T.DatabasesData MiningComputer ScienceArtificial IntelligenceNatural Language & Machine TranslationMachine LearningGraphical & Digital Media Applications3D Graphics & Modelling

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