This notebook presents implementations and experiments for various classical Machine Learning techniques, such as Ordinary Least Squares, Ridge Regression, Expectation Maximization, Full Bayesian Inference, Bayes Classifiers, kNN, and MLP. It's important to note that these implementations were created from scratch. The work within this notebook is directly related to a homework assignment for my MSc in Machine Learning, where I provided step-by-step solutions and explanations for each method.
This project is licensed under the MIT License - see the LICENSE file for details.