# Machine Learning Exercises

This repository contains the Python programming exercises accompanying the theory from my [machine learning book](https://franziskahorn.de/mlbook/). They are part of the curriculum of the [ML for Data Scientists Workshop](https://franziskahorn.de/mlws_scientist.html).

If you have any questions, please send me an [email](mailto:hey@franziskahorn.de).

Have fun!

### Using Python

The programming exercises are written in Python. If you're unfamiliar with Python, you should work through [this tutorial](https://github.com/cod3licious/python_tutorial).

##### Using Python on your own computer
The [Python tutorial](https://github.com/cod3licious/python_tutorial) includes some notes on how to install Python and Jupyter Notebook on your own computer. <br>
Please make sure you're using Python 3 and all libraries listed in the [`requirements.txt`](/requirements.txt) file are installed and up to date. You can verify this with the [`test_installation.ipynb`](/test_installation.ipynb) notebook.

##### Using Google Colab
If you have a Google account, you can also run the code in the cloud using Google Colab:
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cod3licious/ml_exercises) <br>
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 5), 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.