Date  Topic  Assignment Due  Materials 
Mon 31. Aug  Course Introduction, Python Review, Math Review 



Videos:
Resources:

Mon 14. Sept  Math Review: Distributions, Statistics, Vectors, Matrices, Derivative and Optimization 

[Slides]


Videos:
Reading:

Mon 21. Sept  Representations 

[InClass Exercise]


Reading:
Videos:

Wed 23. Sep 
Homework 0 Due: Python / Math Warmup 
[Github] 

Mon 28. Sept  Hypothesis Testing 

[Slides Example]


Videos:
Reading:

Mon 5. Oct  Linear and Logistic Regression 

[Slides Ex]


Reading:
Videos:

Mon 12. Oct  Introducing Deep Learning and PyTorch 

[Example]


Reading:
Videos:

Wed 14. Oct 
Homework 1 Due: Logistic Regression 
[Github] 

Mon 19. Oct  Clustering and Topic Models: Intro 

[Slides] [Inclass Discussion]


Readings:
Videos:

Mon 26. Oct  PyTorch Nuts and Bolts 



Readings:
Videos: (Not by me, this time)

Wed 28. Oct 
Homework 3 Due: Project Proposal 
[Github] 

Mon 2. Nov  Sequence Models 

[Slides] [Inclass Discussion]


Readings:
Required Videos:

Mon 9. Nov  Exam 


Wed 11. Nov 
Homework 2 Due: Logistic Regression Redux 
[Github] 

Mon 16. Nov  Machine Translation, Sequence to Sequence 

[LSTM Example] [Inclass Discussion]


Videos:

Mon 23. Nov  Visualization 

[Slides] [Inclass Discussion]


Reading:
Videos:

Mon 30. Nov  Language Models: Classical to Neural 

[Slides] [Inclass Discussion]


Reading:
Videos:

Mon 7. Dec  Project Presentations 


Thu 17. Dec 
Project Writeups Due 
[Github] 
