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Machine learning course at University of Pavia

Prerequisites

Prerequisites for the course include basic knowledge of GitHub, Colab and python. It is thus required before the course to go through these slides as well as the two python basics notebooks:

  • python_intro_part1.ipynb
    • Quickstart
    • Indentation
    • Comments
    • Variables
    • Conditions and if statements
    • Arrays
    • Strings
    • Loops: while and for
    • Dictionaries
  • python_intro_part2.ipynb
    • Functions
    • Classes/Objects
    • Inheritance
    • Modules
    • JSON data format
    • Exception Handling
    • File Handling

Machine Learning Lectures and Tutorials

Day 1

Day 2

Day 3

Day 4

Day 5

Resources

  • Pattern Recognition and Machine Learning, Bishop (2006)
  • Deep Learning, Goodfellow et al. (2016) -- link
  • Introduction to machine learning, Murray (2010) -- video lectures
  • Stanford ML courses -- link

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