UPDATED on 28/02/2022: This course will start on March, 2nd, 2022, in room C8 from 16.00 to 18.00. The lecture of Friday, 4th, will be in LabInf from 14.00 to 16.00. The recording of the previous year will be available on the new KIRO platform.
All the materials will be distributed via the new KIRO platform at Course 1747. The link will be posted as soon as possible
The notebooks will be available on GitHub at opt4ds. If you want to contribute to the repository, please join the group and commit your improvements.
A complete list of reference books is available on StackExchange
General Readings
Pretty nice video on YouTube:
General reading about Machine Learning topics:
- Evolution of randomness in optimization methods for supervised machine learning
- Adversarial attacks on medical machine learning
- The Softmax function and its derivative
Readings about the Flux Machine Learning Stack:
- Flux website
- Model-building Basic: Taking the gradients
- Reinforcement Learning vs. Differentiable Programming
Interesting Links
- Runge phenomena: Polynomial interpolation at evenly-spaced nodes converges iff the function is analytic inside a football-shaped region.
Useful Links
- Check out the new Operations Research Stack Exchange QnA site from StackExchange.
- The Julia Programming Language
- IAML: Italian Association for Machine Learning
- GitHub Student Pack
- Natural Language Toolkit
- Google Summer of Code
- NumFOCUS: Open Source = Better Science