Created by Philipp Eller ([email protected])
Contents:
| File | Content |
|---|---|
| optimization.ipynb | Basics of optimization algorithms, illustrated using the 2d Rosenbrock test function |
| decorrelation_and_pca.ipynb | De-correlation of datasets and dimensionality reduction via principle component analysis (PCA) |
| clustering_basics.ipynb | Basics of clustering algorithms: k-Means and Gaussian mixture model (GMM) |
| clustering_examples.ipynb | Some more fun applications of clsutering |
| expectation_maximization_1d.ipynb | Extra norebook illustrating the EM algorithm in 1d |
| my_mystery_module.py | Some code used in the clustering notebooks above |
| classification.ipynb | Classification using various algorithms applied to the MNIST dataset |
| regression.ipynb | Regression using various algorithms applied to the Boston housing dataset |
| deep_learning.ipynb | Various Deep Learning Models applied to the MNIST dataset |
| variational_autoencoder.ipynb | Variational auto encoder and generator |
| Exoplanet.ipynb | Data Analysis example for an Exoplanet Analysis |