Skip to content

Machine learning and optimization algorithms from scratch + visualization

Notifications You must be signed in to change notification settings

alami-oussama/Machine-learning-from-scratch

Repository files navigation

Machine learning from scratch

Implementing different machine learning and optimization algorithms from scratch and visualizing them without any machine learning/optimization library.

Implemented machine learning algorithms

  • Perceptron
  • Linear regression
  • Logistic regression
  • Polynomial regression
  • Multiclass classification (One-vs-rest, One-vs-one)
  • Nonlinear transformation

Implemented optimization algorithms

Unconstrained optimization :

  • Gradient descent
  • Newton
  • Line search (Bisection, Newton raphson, False position)
  • Backtracking line search (Armijo, Goldstein, Weak-Wolfe, Strong-Wolfe)

Constrained optimization :

  • Frank-wolfe
  • Feasible directions
  • Projected gradient
  • Reduced gradient