This schedule is tentative and subject to change. Please check back often.
Reading listed for each lecture is not mandatory unless otherwise specified
Legend:
Date  Lecture  Topics  Relevant Reading  Announcements 

Mon 28Aug 
1: Introduction [Slides] 
Introductory Math MLE 
TM : Chapters 1, 2  
Wed 30Aug 
2: Classification [Slides] [Class_Notes] 
KNN  TM : Chapter 8  
Mon 4Sept 
LABOR DAY HOLIDAY 

Wed 6Sept 
3: Naive Bayes [Slides] 
TM : 6.1  6.10  HW1 out  
Mon 11Sept 
4: Decision Trees [Slides] 
TM : Chapter 3  
Wed 13Sept 
5: Linear Regression [Slides] 
TM : Chapter 4.14.3  
Mon 18Sept 
6: Logistic Regression [Slides] 
KM : 8.1  8.3, 8.6  
Wed 20Sept 
7: Perceptron [Slides] 
[10601_Notes] [Barnabas'_Notes]  HW1 due HW2 out 

Mon 25Sept 
8: Neural Networks 1 [Slides] [Matlab_Demos] 
[Online_Book] TM : Chapter 4 CB : Chapter 5 

Wed 27Sept 
9: Neural Networks 2: Deep Learning [Slides] 
[CNN_Notes]
[MLP_Notes] [Perceptron_Notes] [ImageNet_Paper] [Bengio_Deep_Learning] 

Mon 2Oct 
10: Applications of Neural Networks [Slides] 

Wed 4Oct 
11: Support Vector Machines  1 [Slides] 
KM: Chapter 14 CB: Chapters 6 & 7 
HW2 due HW3 out 

Mon 9Oct 
12: Support Vector Machines  2 [Slides] 
[SVM_Projected_Notes]
KM: Chapter 14 CB: Chapters 6 & 7 

Wed 11Oct 
13: Ensemble Learning and Boosting [Slides] 
[Boosting_Projected_Notes]
CB: 14.3 

Mon 16Oct 
14: Active Learning [Slides] 
[Settles_Notes]
[Balcan_Notes] [Krause_2008] 

Wed 18Oct 
15: Unsupervised Learning (Clustering)  1 [Slides] 
[EM_Notes]
[MoG_Notes] 
HW3 due  
Mon 23Oct 
16: Clustering  2 [Slides] 

Wed 25Oct 
MIDTERM 5:00 PM (Location: MM 103 and MM A14) [Google Maps] 
HW4 out  
Mon 30Oct 
17: Dimensionality Reduction  1 (PCA) [Slides] 
[PCA_reading]  
Wed 1Nov 
18: Dimensionality Reduction  2 (ICA) [Slides] 
[ICA_reading]  
Mon 6Nov 
19: Semisupervised Learning [Slides] 
[SSL_Survey]  
Wed 8Nov 
20: Learning Theory  1 [Slides] 
[Learning_Theory_Notes (p119)]  HW4 due  
Mon 13Nov 
21: Learning Theory  2 [Slides] 

Wed 15Nov 
22: Graphical Models (Bayesian Networks) 1 [Slides] 
HW5 out  
Mon 20Nov 
23: Graphical Models (Markov Random Fields)  2 [Slides] [Lecture Video] 

Wed 22Nov 
THANKSGIVING  
Mon 27Nov 
24: Guest Lecture: Zoltán Szabó (CMAP, École Polytechnique) [Slides] 

Wed 29Nov 
25: Hidden Markov Models  1 [Slides] 
[Jordan_GM_Notes]  
Mon 4Dec 
26: Hidden Markov Models  2 [Slides] [Additional_Slides] 
HW5 due  
Wed 6Dec 
27: LargeScale Question Answering on Knowledge Bases and Text 