1. Install latest version of Anaconda 3 from https://www.anaconda.com/
2. Clone the project repository from https://github.com/fedme/ml-assignment-3
3. Open an Anaconda 3 prompt
4. From the prompt, browse to the folder where you cloned the repository
5. Run the following command to create the conda environment:

   conda env create --file=environment.yaml
   

6. Activate the newly created environment:

   activate fmeini3-ml-assignment-3
   

Alternatively, you can install the latest version of the required packages manually from PIP: pip install numpy pandas scipy matplotlib seaborn scikit-learn yellowbrick

Code is divided into multiple python scripts that loosely map the structure of the assignment:

• python clustering.py runs KMeans and EM clustering and generates plots for them (inside the plots folder)
• python dimensionality.py runs PCA, ICA, Randomized Projections, and SVD dimensionality reduction algorithms and generates plots for them (inside the plots folder)
• python clustering_on_reduced_data.py runs KMeans and EM clustering on the dataset with reduced dimensionality and generates plots for them (inside the plots folder)
• python neural_networks.py trains neural network classifiers on many versions of the Fashion MNIST dataset (base, reduced, augmented with clusters) and generates plots for them (inside the plots folder)
• The other scripts are used to transform and save data. It is not necessary to run them, since all the data is already present inside the data folder.