Machine Learning Techniques for Text: Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation

Nikos Tsourakis Machine Learning Techniques for Text Reviews Summary

Ratings Breakdown

Rated 4.8 by 8 people

Pros from Reviews

  • Balanced understanding and application
  • Clear explanations and examples
  • Covers a variety of techniques
  • Practical examples and case studies
  • Accessible to readers with different backgrounds
  • Learn how to acquire and process textual data
  • Obtain deeper insight into commonly used algorithms
  • Implement models for solving real-world problems

Cons from Reviews

    None found

Notable Features

Text Processing
Dimensionality Reduction
Classification
Evaluation
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