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100JoursDeML

100JoursDeML is a personal challenge to explore machine learning topics over one hundred days. The repository collects the notebooks and slides used during the journey. Most of the material is in French and follows the companion YouTube playlist.

Directory overview

Directory Topics covered
01_Debuter_En_Python Getting started with Python, NumPy, Pandas and basic visualization
02_Statistiques_Pour_Le_Machine_Learning Statistics fundamentals for machine learning
03_Preprocessing Data cleaning, missing value treatment and normalization
04_Selection_Features Manual and automatic feature selection techniques
05_Apprentissage_Supervise Supervised learning algorithms and model validation
06_Apprentissage_Non_Supervisé Clustering and other unsupervised methods
07_Series_Temporelles Time series analysis including ARIMA, VAR, VECM and GARCH
08_NLP Introduction to natural language processing and sentiment analysis

Running the notebooks

  1. Install Python 3.8 or later.

  2. Install commonly used packages:

    pip install numpy pandas matplotlib seaborn scikit-learn statsmodels nltk jupyter

  3. Launch Jupyter from the repository root:

    jupyter notebook

    Open the notebook you wish to run from the browser interface.

License

No license file is provided at the moment. If you wish to reuse the content, please contact the repository maintainers for clarification.

Contributing

Contributions are welcome via pull requests. Feel free to submit fixes or improvements.