AML-19-20-notes

This is a summary of the material proposed by prof. Fabio Galasso in the course Adavanced Machine Learning, held at Sapienza University of Rome in A.A. 2019/2020. Original sources and authors are indicated in the slides provided by the prof. These nodes are shared without any guarantee of complete correctness, since I may have done typos or misunderstood something. Feel free to drop an email at giovannificarra95@gmail.com to report errors, or contribute to this repo.

Following, the topics covered by these notes:

1. Introduction to Machine Learning
2. Basics of digital image filtering
3. Object Instance Identification using Color Histograms
4. Performance evaluation
5. Image Classification
6. Introduction to Deep Learning and PyTorch
7. Convolutional Neural Networks
8. Training Neural Networks
9. Detection and Segmentation
10. Visual search, object retrieval and person re-identification
11. Pose estimation
12. Sequence Modeling and Forecasting
13. Multi-Task and Meta Learning