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Hsiao's Data Science from Scratch Notebook

from:Data Science from Scratch

Book of Contents(Finish Time)

  1. Introduction (2017/03/09)
  2. A Crash Course in Python (2017/03/16)
  3. Visualizing Data (2017/03/23)
  4. Linear Algebra (2017/03/30)
  5. Statistics (2017/03/30)
  6. Probability (2017/04/06)
  7. Hypothesis and Inference (2017/04/06)
  8. Gradient Descent (2017/04/13)
  9. Getting Data (2017/04/27)
  10. Working With Data (2017/05/04)
  11. Machine Learning (2017/05/11)
  12. k-Nearest Neighbors (2017/05/11)
  13. Naive Bayes (2017/05/11)
  14. Simple Linear Regression (2017/05/11)
  15. Multiple Regression (2017/05/18)
  16. Logistic Regression (2017/05/18)
  17. Decision Trees (2017/05/25)
  18. Neural Networks (2017/05/25)
  19. Clustering (2017/06/01)
  20. Natural Language Processing (2017/06/01)
  21. Network Analysis
  22. Recommender Systems
  23. Databases and SQL
  24. MapReduce
  25. Go Forth And Do Data Science

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The MIT License

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