Schedule

1	Oct 3 / 4	Introduction (CP) pdf	Basics (TM) pdf Chapter 1 (Bishop)
2	Oct 10 / 11	Basics (TM) (cont.) pdf Chapter 1 (Bishop)	Linear Models for Regression (TTW) pdf Chapter 3 (Bishop)
	Oct 11	A0 Due: Mathematical Prerequisites
3	Oct 17 / 18	Advanced Regression (TTW) pdf Chapter 3 (Bishop)	Linear models for classification (TTW) pdf Chapter 4 (Bishop) or Chapter 4 (Hastie et al.)
4	Oct 24 / 25	Python tutorial moodle	Linear models for classification (TM) (cont.) pdf Chapter 4 (Bishop) or Chapter 4 (Hastie et al.)
5	Oct 31 / Nov 1	Linear models for classification (TM) (cont.) pdf Chapter 4 (Bishop) or Chapter 4 (Hastie et al.)	All Saint's Day
	Oct 31	A1 Due: Lab Regression
6	Nov 7 / 8	Neural networks (TTW) orig pdf new pdf Chapter 5 (Bishop) or Chapter 11 (Hastie et al.)	Kernel methods (TTW) pdf Chapter 6 (Bishop)
7	Nov 14/ 15	Sparse kernel machines (TM) pdf Chapter 7 (Bishop) or Chapter 12 (Hastie et al.)	Sparse kernel machines (TTW) (cont.) pdf Chapter 7 (Bishop) or Chapter 12 (Hastie et al.)
8	Nov 21 / 22	Graphical models (TTW) pdf Chapter 8 [8.1, 8.2] (Bishop) or Chapter 17 (Hastie et al.)	Preparation midterm exam
	Nov 22	A2 Due: Pen & Paper 1
9	Nov 28/ 29	Ethics of machine learning (TTW)	Midterm exam
10	Dec 5 / 6	Association Analysis -- Part 1 (CP) pdf	Association Analysis -- Part 2 (CP) pdf
	Dec 5	A3 Due: Lab Classification
11	Dec 12 / 13	Dimensionality Reduction (KS) pdf	Clustering (CP) pdf
	Dec 19 / 20	Merry Christmas!	Merry Christmas!
	Dec 26 / 27	Merry Christmas!	Merry Christmas!
	Jan 2 / 3	Happy New Year!	Happy New Year!
12	Jan 9 / 10	Clustering (CP) pdf	Clustering (CP) pdf Discussion Lab (CH)
	Jan 9	A4 Due: Lab Clustering
13	Jan 16 / 17	Clustering (CP) pdf	Clustering (CP) pdf
14	Jan 23 / 24	Outlier Detection (CP) pdf Discussion Pen & Paper (BS)	Outlier Detection (CP) pdf Preparation final exam
	Jan 23	A5 Due: Pen & Paper 2
15	Jan 30 / 31	Outlook	Final exam