Python for Machine Learning and Data Science

Materials for the "Python in Machine Learning" PhD course offered at the Medical University Graz.

Installing Python & Jupyter

To install Python, follow the instructions on python.org - note that the instructions vary by operating system.

Oncee you have installed Python, you can install Jupyter, and all the requirements for this course, by first downloading the requirements.txt file from this repository and running:

pip install -r requirements.txt

from the command line. This will install Jupyter and all other requirements that are listed in the requirements.txt file.

Alternatively, you can install the requirements by copying and pasting the following in to the command line:

pip install ipython jupyter numpy pandas scikit-learn xgboost matplotlib biopython scipy pillow opencv-python seaborn graphviz

Note: you may need to install the Graphviz binaries in addition to the Python version.

Once you have installed Jupyter, you can run the following to start a local Jupyter server which will open in the default browser:

jupyter lab

If a browser window does not open automatically, you will need to copy the URL printed to the console and open this in a browser. Typically this URL is http://localhost:8888

Note: it is good practice to create a virtual environment for every project that you create, if you wish to do so, see the Python venv command, detailed instructions can be found here: https://docs.python.org/3/library/venv.html - however, for the purposes of this course it is not a requirement that you use a virtual environment.

Online Alternatives

If you cannot install Python locally for whatever reason, you can use Google Colab as an alternative. See https://colab.research.google.com - you will need a Google account to use this service.

Note that the modul17.com server does not run outside of the seminar class times.

Course Contents

The following is a list of the contents of the course, with links to the relevant notebooks where applicable.

• What is Machine Learning?
• Terminology
  • Fitting a line to some data
• NumPy
• Sci-Kit Learn
• Machine Learning
  • Classification
  • Regression
  • Supervised vs. Unsupervised
  • Clustering
• Algorithms
  • Linear Regression
  • Logistic Regression
  • Decision Trees and Random Forests
  • Support Vector Machines
• Image Analysis
  • PyTorch
  • MedMNIST
• Bioinformatics

License

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