https://github.com/philippeller/teaching
https://github.com/philippeller/teaching
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/philippeller/teaching
- Owner: philippeller
- License: apache-2.0
- Created: 2020-08-25T13:20:46.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2022-09-22T16:16:17.000Z (over 2 years ago)
- Last Synced: 2025-02-01T12:45:28.683Z (4 months ago)
- Language: Jupyter Notebook
- Size: 34.8 MB
- Stars: 10
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Teaching Material for Numerical Methods and Machine Learning
Created by Philipp Eller ([email protected])
Contents:
File | Content
--- | ---
[optimization.ipynb](https://github.com/philippeller/Teaching/blob/master/optimization.ipynb) | Basics of optimization algorithms, illustrated using the 2d Rosenbrock test function
[decorrelation_and_pca.ipynb](https://github.com/philippeller/Teaching/blob/master/decorrelation_and_pca.ipynb) | De-correlation of datasets and dimensionality reduction via principle component analysis (PCA)
[clustering_basics.ipynb](https://github.com/philippeller/Teaching/blob/master/clustering_basics.ipynb) | Basics of clustering algorithms: k-Means and Gaussian mixture model (GMM)
[clustering_examples.ipynb](https://github.com/philippeller/Teaching/blob/master/clustering_examples.ipynb) | Some more fun applications of clsutering
[expectation_maximization_1d.ipynb](https://github.com/philippeller/Teaching/blob/master/expectation_maximization_1d.ipynb) | Extra norebook illustrating the EM algorithm in 1d
[my_mystery_module.py](https://github.com/philippeller/Teaching/blob/master/my_mystery_module.py) | Some code used in the clustering notebooks above
[classification.ipynb](https://github.com/philippeller/Teaching/blob/master/classification.ipynb) | Classification using various algorithms applied to the MNIST dataset
[regression.ipynb](https://github.com/philippeller/Teaching/blob/master/regression.ipynb) | Regression using various algorithms applied to the Boston housing dataset
[deep_learning.ipynb](https://github.com/philippeller/Teaching/blob/master/deep_learning.ipynb) | Various Deep Learning Models applied to the MNIST dataset
[variational_autoencoder.ipynb](https://github.com/philippeller/Teaching/blob/master/variational_autoencoder.ipynb) | Variational auto encoder and generator
[Exoplanet.ipynb](https://github.com/philippeller/Teaching/blob/master/Exoplanet.ipynb) | Data Analysis example for an Exoplanet Analysis