# Important Links

- Download PDF of Syllabus
- Link to Piazza Class
- Link to submit GitHub username
- Scanning - Gradescope
- Submitting - Gradescope
- Scholar Computing Cluster (some nodes with GPUs)

## Optional textbooks

The bracketed acronym is used for referencing these books in the schedule below.

- [DL]
*Deep Learning*by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, 2016. http://www.deeplearningbook.org - [ML]
*Machine Learning: A Probabilistic Perspective*by Kevin P. Murphy, 2012. https://ebookcentral.proquest.com/lib/purdue/detail.action?docID=3339490 - [PY]
*Python Data Science Handbook*by Jake VanderPlas, 2016. https://jakevdp.github.io/PythonDataScienceHandbook/

# Course Schedule (Tenative)

L | W | Day | Date | Due by noon | Topic | Related readings |

1 | 1 | Mon | Aug-19 | Syllabus | ||

2 | Wed | Aug-21 | Introduction to A.I. | [slides] Intro. to A.I., DARPA Overview of AI | ||

3 | Fri | Aug-23 | How to Select Papers / Overview of A.I. Topics | [slides] How to Select Papers, [slides] Overview of A.I. Topics | ||

4 | 2 | Mon | Aug-26 | Intro. to ML | [ML, Ch. 1], [slides] Intro. to Machine Learning | |

5 | Wed | Aug-28 | [Quiz 1] | (continued) | HW1 Instructions, [slides] Intro. to Machine Learning (part 2) | |

6 | Fri | Aug-30 | Clustering | [notebook], [pdf of notebook] | ||

3 | Mon | Sep-2 | No class (Labor Day) | |||

7 | Wed | Sep-4 | HW1 | Clustering (continued) | [notebook], [pdf of notebook] | |

8 | Fri | Sep-6 | Select 3 papers | Clustering (continued) | [notebook], [pdf of notebook] | |

9 | 4 | Mon | Sep-9 | Brief Review of Linear Algebra | [DL, Ch. 2], [notebook], [pdf of notebook] | |

10 | Wed | Sep-11 | [Quiz 2] | Brief Review of Linear Algebra (continued) | HW2 Instructions, [notebook], [pdf of notebook] | |

11 | Fri | Sep-13 | Brief Review of Linear Algebra (continued) | [notebook], [pdf of notebook] | ||

12 | 5 | Mon | Sep-16 | Review of Probability | [DL, Ch. 3], [ML, Ch. 2], [slides] Review of Probability (Part 1) | |

13 | Wed | Sep-18 | Review of Probability (continued) | [DL, Ch. 3], [ML, Ch. 2], [slides] Review of Probability (Part 2) | ||

14 | Fri | Sep-20 | HW2 | Review of Probability (continued) | [DL, Ch. 3], [ML, Ch. 2], [slides] Review of Probability (Part 3) | |

15 | 6 | Mon | Sep-23 | [Quiz 3] | Review of Probability (continued) | [DL, Ch. 3], [ML, Ch. 2], [slides] Review of Probability (Part 4) |

16 | Wed | Sep-25 | Density Estimation | [slides] Density Estimation (Part 1) | ||

17 | Fri | Sep-27 | Density Estimation (continued) | [slides] Density Estimation (Part 2) | ||

18 | 7 | Mon | Sep-30 | Density Estimation (continued) | [ML, Ch. 4], [slides] Density Estimation (Part 3) | |

19 | Wed | Oct-2 | [Quiz 4] | Gaussian Mixture Models | [ML, Ch. 11], [PY 05.12], [slides] Gaussian Mixture Models (Part 1) | |

20 | Fri | Oct-4 | Gaussian Mixture Models (continued) | [slides] Gaussian Mixture Models (Part 2) | ||

8 | Mon | Oct-7 | No class (Oct Break) | |||

21 | Wed | Oct-9 | Optimization | [DL, Ch. 4], [slides] Optimization, [notebook] NumPy Gradient Descent | ||

22 | Fri | Oct-11 | Optimization/PyTorch (continued) | [notebook] PyTorch Gradient Descent | ||

23 | 9 | Mon | Oct-14 | Optimization/PyTorch (continued) | [notebook] PyTorch Gradient Descent | |

24 | Wed | Oct-16 | [Quiz 5] | Optimization/PyTorch (continued) | [notebook] PyTorch Gradient Descent | |

25 | Fri | Oct-18 | Convolutional Networks | HW3 Instructions, [notebook] Convolutionals | ||

26 | 10 | Mon | Oct-21 | Convolutional Networks (continued) | Illustrations of various convolutions, Paper corresponding to illustrations | |

27 | Wed | Oct-23 | Convolutional Networks (continued) | [notebook] Convolutionals, [notebook] CIFAR-10 Tutorial, [pdf of notebook] Convolutionals, [pdf of notebook] CIFAR-10 Tutorial | ||

28 | Fri | Oct-25 | Generative Adversarial Networks (GAN) | [slides] GANs | ||

29 | 11 | Mon | Oct-28 | HW3 | Deep Convolutional GANs | [slides] DCGAN, [notebook] DCGAN Tutorial (edited for MNIST), [pdf of notebook] DCGAN Tutorial (edited for MNIST), PyTorch Tutorial on DCGAN for faces, DCGAN Original Paper |

30 | Wed | Oct-30 | Invertible Normalizing Flows | [slides] Normalizing Flows, [notebook] Change of Variables, [pdf of notebook] Change of Variables, GLOW paper | ||

31 | Fri | Nov-1 | [Quiz 6] | Invertible Normalizing Flows (continued) | ||

32 | 12 | Mon | Nov-4 | Invertible Normalizing Flows (continued) | Project Submission Instructions, [slides] Normalizing Flows | |

33 | Wed | Nov-6 | Density Destructors | [slides] Density Destructors | ||

34 | Fri | Nov-8 | Density Destructors (continued) | [slides] Density Destructors, [code] Density Destructor Code | ||

35 | 13 | Mon | Nov-11 | [Quiz 7] | Unsupervised Dimensionality Reduction/PCA | [slides] PCA (and a few project notes) |

36 | Wed | Nov-13 | PCA | [slides] PCA (and a few project notes), [notebook] PCA Demos | ||

37 | Fri | Nov-15 | Term paper/Code | Autoencoders | Project Submission Instructions, [slides] Autoencoders | |

14 | Mon | Nov-18 | Presentations | |||

Wed | Nov-20 | Presentations | ||||

Fri | Nov-22 | 5-min video | Presentations | |||

15 | Mon | Nov-25 | Presentations | |||

Wed | Nov-27 | No class (Thanksgiving) | ||||

Fri | Nov-29 | No class (Thanksgiving) | ||||

16 | Mon | Dec-2 | Presentations | |||

Wed | Dec-4 | Presentations | ||||

Fri | Dec-6 | Reviews | Presentations | |||

Mon | Dec-9 | No exam | ||||

Wed | Dec-11 | No exam | ||||

Fri | Dec-13 | No exam |