Szczegóły ebooka

Learning Data Mining with Python. Use Python to manipulate data and build predictive models - Second Edition

Learning Data Mining with Python. Use Python to manipulate data and build predictive models - Second Edition

Robert Layton

Ebook
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK.
You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.
With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
  • 1. Getting Started with data mining
  • 2. Classification using scikit-learn estimators
  • 3. Predicting Sports Winners with Decision Trees
  • 4. Book Recommendations using Affinity Analysis
  • 5. Features and scikit-learn transformers
  • 6. Social media spam detection using Naive Bayes
  • 7. Follow recommendations using graph mining
  • 8. Beating CAPTCHAs with Neural Networks
  • 9. Authorship attribution
  • 10. Clustering news articles
  • 11. Object Detection in images using Deep Neural Networks
  • 12. Working with Big Data
  • 13. Appendix: Next Steps
  • Tytuł: Learning Data Mining with Python. Use Python to manipulate data and build predictive models - Second Edition
  • Autor: Robert Layton
  • Tytuł oryginału: Learning Data Mining with Python. Use Python to manipulate data and build predictive models - Second Edition
  • ISBN: 9781787129566, 9781787129566
  • Data wydania: 2017-04-27
  • Format: Ebook
  • Identyfikator pozycji: e_15iq
  • Wydawca: Packt Publishing