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Machine Learning Algorithms from Scratch

Had some fun coding some known classification and regression models from scratch. Included some explanation to illustrate functionalities of each, and experiemented with different variables to illustrate characteristics

NOTE: This was done purely for the purpose of exploration so I cannot guarentee that there are 0 bugs/errors. These were also not written at a presentation-level, so stylistically it will not be the most beautiful piece of code you've ever seen.

Regression Projects include:

  1. Least Squares
  2. MAP (Poly)
  3. Gaussian and Sigmoid Basis Functions
  4. Full Bayesian Inference
  5. Bayesian Sequential Learning
  6. Predictive Distribution
  7. Gaussian Processes

Classification Projects include:

  1. Least Squares
  2. Predictive Distribution
  3. Gaussian Processes

** Might update with more algos in the future :D **