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A series of self-correcting challenges for practicing your ML and Deep Learning skills
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Machine Learning Katas

stability-wip PRs Welcome

This repository contains a series of exercises for practicing your ML and Deep Learning skills, under the form of self-correcting Jupyter notebooks.

It is part of the Machine Learning course taught at the Graduate School of Cognitive Engineering (ENSC).

ENSC logo


Index by exercise type

Working with Data Classic Datasets Kaggle Datasets
Tensor Management Fashion-MNIST Dogs vs. Cats
Data Analysis Iris
Breast Cancer
Boston Housing
Reuters News

Index by dataset type

Numerical Data Images Text
Iris Fashion-MNIST Reuters News
Breast Cancer CIFAR10
Boston Housing Dogs vs. Cats

How to run the notebooks

  • Launch an executable version of a notebook in Colaboratory (Google account needed) by opening it and clicking this button: Open In Google Colaboratory

  • Clone or download this repository and run a Jupyter notebook server on your local machine.

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