Pattern Analysis and Machine Intelligence (2015-2016)
The objective of this course is to give an advanced presentation, i.e., a statistical perspective, of the techniques most used in artificial intelligence and machine learning for pattern recognition, knowledge discovery, and data analysis/modeling.
This page is devoted to the labs part of PAMI. If you want more information about the course please check this page.
News
- Jan 17, 2015: The second homework is online.
- Jan 11, 2015: The first homework is online.
- Dec 22, 2015: Material for Lab10 is online.
- Dec 15, 2015: Material for Lab09 is online.
- Dec 1, 2015: Material for Lab08 is online.
- Nov 30, 2015: Material for Lab07 is online.
- Nov 20, 2015: Material for Lab06 is online.
- Nov 16, 2015: Material for Lab05 is online.
- Nov 09, 2015: Material for Lab04 is online.
- Nov 03, 2015: Material for Lab03 is online.
- Nov 02, 2015: Material for Lab02 is online.
- Oct 12, 2015: Material for Lab01 is online.
- Oct 12, 2015: The new labs started. Enjoy!
Material
- R for Matlab users
- Lab 1: Introduction to R (material + links)
- Lab 2: Questions and exercises on statistical learning (material)
- Lab 3: First exercises on linear regression (material, t-statistics table)
- Lab 4: Multiple linear regression (material)
- Lab 5: Advanced linear regression (material), Introduction to Clustering and K-Means(slides, handouts)
- Lab 6: Clustering: K-Medoids, Fuzzy C-Means, and Hierarchical (slides, handouts)
- Lab 7: Clustering: GMM, DBSCAN, and Jarvis-Patrick (material, slides, handouts)
- Lab 8: Clustering: spectral clustering (introduction, multimodal), evaluation (material, slides, handouts)
- Lab 9: Classification: logistic regression (material)
- Lab 10: Classification: LDA, QDA, KNN (material)