Pattern Analysis and Machine Intelligence (2014-2015)
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 26, 2014: Material for Lab10 is online.
- Jan 20, 2014: The fourth homework is out.
- Jan 19, 2014: Material for Lab08 and Lab09 is online.
- Jan 14, 2014: Material for Lab07 is online.
- Jan 12, 2014: The third homework is out.
- Jan 9, 2014: The second homework is out.
- Jan 5, 2015: Happy New Year! The first homework is out, check here.
- Dec 15, 2014: Material for Lab06 is online.
- Dec 1, 2014: Material for Lab05 is online.
- Nov 17, 2014: Material for Lab04 is online.
- Nov 3, 2014: Material for Lab02 and Lab03 is online.
- Oct 24, 2014: Material for Lab01 is online.
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)
- Lab 4: Multiple linear regression (material)
- Lab 5: Advanced linear regression + Classification basics (material)
- Lab 6: Classification: Logistic Regression, LDA, QDA, KNN (material)
- Lab 7: Clustering: intro and K-means (slides, handouts)
- Lab 8: Clustering: K-Medoids, Fuzzy C-Means, and Hierarchical(slides, handouts)
- Lab 9: Clustering: Mixture of Gaussians, DBSCAN, and Jarvis-Patrick(slides, handouts)
- Lab 10: Clustering: evaluation (slides, handouts, spectral Clustering)