machine-learning-1

Code and notebooks based on the material for the ML1 course I took at the University of Amsterdam.

Install

To get a reproducible environment, first install Conda or Miniconda and then, create a new environment with the requirements with

$ conda env create -f environment.yml

Notebooks

# Activate the environment
$ source activate machine-learning-1
# Explore the notebooks
$ jupyter notebook

• Maximum a posteriori signal detection
• Linear models for regression
• Predicting House Prices With Linear Regression
• Bayesian Linear Regression
• Dimensionality reduction and classification with Fisher's linear discriminant
• Principal Component Analysis
• Neural networks with NumPy
• Expectation Maximization