Machine Learning Feynman Experience: build models from scratch on Google Colab

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https://github.com/leandromineti/ml-feynman-experience

Machine Learning Feynman Experience

Machine Learning Feynman Experience: build models from scratch on Google Colab

"What I cannot create, I do not understand" - Feynman.

This is a collection of concepts I tried to implement using only Python , NumPy and SciPy on Google Colaboratory . If you want to play with the code, feel free to copy the notebook and have fun.

Notebooks

Work in progress

To do

  • Principal component analysis
  • Linear discriminant analysis
  • Central limit theorem
  • Single parameter bayesian inference
  • Decision tree
  • Random Forest
  • Support vector machine
  • Perceptron
  • Gradient boosting machine
  • Autoregressive models

Contributions

If you spot a mistake or omission, please feel free to create a new issue.

References

  • Casella, G., & Berger, R. L. (2002). Statistical inference (Vol. 2). Pacific Grove, CA: Duxbury.
  • DeGroot, M. H., & Schervish, M. J. (2012). Probability and statistics. Pearson Education.
  • Hastie, T., Tibshirani, R., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction (2nd ed). New York, NY: Springer.
  • Cover image : Dr. Richard Feynman during the Special Lecture: the Motion of Planets Around the Sun . Public Domain. Created: 13 March 1964.

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