Differences

This shows you the differences between two versions of the page.

--- start [2023/07/03 18:09] – anderson
+++ start [2023/08/11 12:37] – [August] anderson
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 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 1:\\  Aug 22, 24   |  | | |
+| Week 1:\\  Aug 22, 24   | Course overview. Jupyter notebooks. Simple neural networks.   | | [[https://www.freecodecamp.org/news/exploratory-data-analysis-with-numpy-pandas-matplotlib-seaborn/|What is Data Analysis? How to Visualize Data with Python, Numpy, Pandas, Matplotlib & Seaborn Tutorial]], by Aakash NS| Not graded: Please fill out [[https://forms.gle/hppJ5QuRFuRn1L2h7|this anonymous survey]] before Thursday class.  |
-| Week 2:\\  Aug 29, 30  |  | | |
+| Week 2:\\  Aug 29, 30  | Regression. Introduction to neural networks. Jupyter notebook animations.   | | |
 ===== September =====
@@ Line 30: / Line 30: @@
 |< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 3:\\  Sept 5, 7  |  | | | |
+| Week 3:\\  Sept 5, 7  | Python clases. Design of NeuralNetwork class.   | | | |
-| Week 4:\\  Sept 12, 14   |  | | |
+| Week 4:\\  Sept 12, 14   | Optimizers.  | | |
-| Week 5:\\  Sept 19, 21  |  | | |
+| Week 5:\\  Sept 19, 21  | Introduction to classification.  | | |
-| Week 6:\\  Sept 26, 28  |  | | |
+| Week 6:\\  Sept 26, 28  | Classification. Convolutional neural networks.  | | |
 ===== October =====
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 |< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 7:\\  Oct 3, 5  |  | | |
+| Week 7:\\  Oct 3, 5  | Introduction to Jax and Pytorch.  | | |
-| Week 8:\\  Oct 10, 12  |  | | |
+| Week 8:\\  Oct 10, 12  | More convolutional neural networks.  | | |
-| Week 9:\\  Oct 17, 19  | | | |
+| Week 9:\\  Oct 17, 19  | Introduction to reinforcement leanring. Learning to play games. | | |
-| Week 10:\\  Oct 24, 26  |  | | |
+| Week 10:\\  Oct 24, 26  | Reinforcement learning for control of dynamic systems.  | | |
 ===== November =====
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 |< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 11:\\  Oct 31 Nov 2  |  | | |
+| Week 11:\\  Oct 31 Nov 2  | Recurrent neural networks.  | | |
-| Week 12:\\  Nov 7, 9  | | | |
+| Week 12:\\  Nov 7, 9  | Unsupervised learning. Dimensionality reduction. Autoencorders. | | |
-| Week 13:\\  Nov 14, 16  |  | | |
+| Week 13:\\  Nov 14, 16  | Clustering.  | | |
 | Fall Break:\\ Nov 20-24 | No classes  |
-| Week 14:\\  Nov 28, 30  | | | |
+| Week 14:\\  Nov 28, 30  | Ensemble methods. Mixture-of-experts. Transformers.  | | |
 ===== December =====
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 |< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 15:\\  Dec 5, 7  | | | |
+| Week 15:\\  Dec 5, 7  | Other topics in current research.  | | [[https://www.cs.colostate.edu/~anderson/cs545/notebooks/2023_AI-scientists-topline-report81.pdf|AI Scientists’ Perspectives on AI]]  |
 | Dec 11-15  |  Final Exam Week  |  No Exams in this course  |