This repository contains the Python programming exercises accompanying the theory from my machine learning book. They are part of the curriculum of the ML for Data Scientists and ML in Practice Workshops.

If you have any questions, please send me an email.

Have fun!

Using Python

The programming exercises are written in Python. If you're unfamiliar with Python, you should work through this tutorial first.

Working on your own computer

The Python tutorial includes some notes on how to install Python and Jupyter Notebook on your own computer.
Please make sure you're using Python 3 and all libraries listed in the requirements.txt file are installed and up to date. You can verify this with the test_installation.ipynb notebook.

Working in the cloud

Using Google Colab

If you have a Google account, you can also run the code in the cloud using Google Colab:
While Google Colab already includes most packages that we need, should you require an additional library (e.g., skorch for training PyTorch neural networks in notebook 6), you can install a package by executing !pip install package in a notebook cell. With Colab, it is also possible to run code on a GPU, but this has to be manually selected.

Using MyBinder

If you don't have a Google account, you can also use MyBinder, which does not require you to log in:
However, this will take a while to load and might be very slow or even crash due to insufficient RAM for some of the exercises.