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GitHub repository for participants of the "Machine learning with Python" training.For information on the training, see the websitehttps://gjbex.github.io/Machine-learning-with-Python/

1. machine_learning_with_python.pptx: PowerPointpresentation used for the training.
2. hands-on: Jupyter notebooks for hands-on sessions.
3. source-code: sample code written to develop the slides andillustrate concepts.
4. environment.yml: conda environment file intended to becross-platform.
5. machine_learning_with_python_linux64_conda_specs.txt:conda environment specification file specific for 64-bit Linux to preciselyreproduce the environment on which the code was developed.
6. License: license information for the material in this repository.
7. Contributing: information on how to contribute to thisrepository.
8. docs: directory containing the website for this repository.
9. Code of conduct: when participating in this trainingyou accept to abide by the code of conduct.

Video recordings of this training are available on YouTube.Note: therecordings were made in 2020 and have not been updated since.

1. Introduction (25 minutes)
2. scikit-learn: data pipelines and regression (28 minutes)
3. scikit-learn: classification and clustering (12 minutes)
4. keras: introduction to neural networks (13 minutes)
5. keras: multilayer perceptrons for digit recognition (34 minutes)
6. [keras: convolutional neural networks for digit recognition] (19 minutes)
7. keras: recurrent neural networks for sentiment classification (26 minutes)