Useful online resources to start

Some fundamentals things you should know about machine learning - with particular focus on Neural Network architectures.

This is a biased view (shared on 17/01/2024),  this is how I would teach this topic.

Note that this serves as intro to the FCNN slides (the ones below) - so many other cool topics in ML (e.g. Gaussian Processes!) are not discussed. 

I would be happy to receive your feedback for improving this slides deck (and yes, normally the slides are presented with transitions : )).

All you needed to start understanding Fully Connected Neural Networks in 41 slides 

This is a biased view (shared on 10/01/2024),  this is how I would teach this topic.
I would be happy to receive your feedback for improving this slides deck (and yes, normally the slides are presented with transitions : )).

All you needed to start understanding Convolutional Neural Networks in 44 slides 

This is a biased view (shared on 24/01/2024),  this is how I would teach this topic.
I would be happy to receive your feedback for improving this slides deck (and yes, normally the slides are presented with transitions : )).

A concise summary of what is Scientific ML, Physics-Enhanced ML and the use of PINNs for ODE and PDE investigations... with application in mechanics and materials in less than 42 slides!

This is a biased view (shared on 31/01/2024),  this is how I would teach this topic.
I would be happy to receive your feedback for improving this slides deck (and yes, normally the slides are presented with transitions : )). If anything is missing, or is not clear, please, let me know. 

Note:

•  the material builds up on the content of the slides deck share before this on Intro to ML, FCNN and CNN

• there is also an entire page dedicated to PEML in this website.