Some tools to help to understand some ML-algorithms
If you'd like to execute the notebooks, please install the requirements.txt.
pip install -r requirements.txt
You will find (in the corresponding folder) a notebook that explains step by step the operations which lead to dimensionality reduction using either Principal Component Analysis or Fisher Linear Discriminant Analysis. You can although directly open the html in your browser.
You will find a notebook that contains tools to visualize the update of a Dense Neural Network during its backpropagation. A set of hyperparameters is here to be changed and to see the impact on the backpropagation process.
Here is the result of an overfitting set of hyperparameters:
