Code for the Machine Learning 1 course of the MSc in Artificial Intelligence at the University of Amsterdam.
Polynomial Regression, Tikhonov Regularization, k-fold cross validation, Bayesian linear regression
Multi-class logistic regression with stochatic gradient descent, Multi-layer perceptrons, MAP optimization,
Gaussian processes, sampling, predictive distribution, hyperparameter learning
Refer to each lab and run the iPython notebook as follows.
jupyter notebook $notebook_name$.ipynb
Python 2.7: Matplotlib, NumPy, SciPy, gzip, cPickle
Copyright © 2017 Dana Kianfar and Mircea Mironenco.
This project is distributed under the MIT license. Please review the UvA regulations governing Fraud and Plagiarism in case you are a student at the UvA.