Documentation of the VU Hands on Machine Learning

This is the documentation of the VU 2.0 ECTS Hands on Machine Learning course at the University of Applied Arts Vienna (short: dieAngewandte). This is the first (and experimental) iteration of this course, starting in summer term 2023.

Refer to the session chapters to follow up on what we did in the specific sessions, and check out the general references section for further material.

Contents:

• Kick-off session
• Session 2 : Setup & Python basics
  • Setup
  • Python basics crash course I
• Session 3 : Python basics recap, loops, functions
  • Loops
  • Functions
• Session 4 : Reading and analysing .csv data sets
  • Fictional scenario
  • Reading local .csv and initial analysis
  • Fetching online .csv and basic plots
  • Exercise 1 - Basic Python applied to data wrangling
• Session 5: Pretty Plotting Pandas
  • Exercise 2 - Pretty plotting with Pandas
  • Demo example
• Session 6: Perceptrons in Python Practice
  • Simple percepton NAND demo
• Session 7: Getting into linear regression
  • Some theory first
  • Coding ML from scratch
  • Comparisons and improvements
• Session 8: Linear regression continued
  • Exercise 3 - Go with the tensor flow
• Session 9: Excursion
• Session 10: Neural networks and course/project reflections
  • Neural networks
  • Course reflection and project ideas
• References
  • Core Topic
  • Python Basics
  • Official Python Documentation
  • Tools
  • Extended Materials
• Notes on grading
  • Notes on the final project
  • Notes on nitpickyness and transparency

This documentation was produced with Sphinx, the Python Documentation Generator. Sphinx itself is written in Python and can be installed with pip install sphinx. Additionally, for this specific docs, also the MyST Parser is used in order to write the section files in Markdown. linkify-it-py is used so that URLs are automagically converted to links. For the theme I am relying on the good old sphinx_rtd_theme, which is used by many open source projects for their documentation on readthedocs.io. This is extended by sphinx_rtd_dark_mode, so that readers get the option to switch between a light and dark mode (see the round button with the moon/sun symbole in the lower right corner of the browser tab). Theme related links can be found in the footer..

The source of this documentation, including the sphinx config used to generate this output, is available under a CC-BY-SA 4.0 license on https://gitlab.com/jackieklaura/hands-on-machine-learning