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

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

Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
data		data
discriminant_analysis		discriminant_analysis
features		features
linear_models		linear_models
metrics		metrics
mixture_models		mixture_models
neural_networks		neural_networks
.gitignore		.gitignore
.travis.yml		.travis.yml
00-matched-filter.ipynb		00-matched-filter.ipynb
01-lr_ex.ipynb		01-lr_ex.ipynb
02-lr_housing.ipynb		02-lr_housing.ipynb
03-bayes_lr_ex.ipynb		03-bayes_lr_ex.ipynb
04-fisher-example.ipynb		04-fisher-example.ipynb
05-pca_ex.ipynb		05-pca_ex.ipynb
06-neural-networks-numpy.ipynb		06-neural-networks-numpy.ipynb
07-expectation-maximization.ipynb		07-expectation-maximization.ipynb
LICENSE		LICENSE
README.md		README.md
environment.yml		environment.yml
graph-latent.png		graph-latent.png
graph-simple.png		graph-simple.png
notebooks_test.py		notebooks_test.py