Differences

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

--- start [2023/08/11 12:37] – [August] anderson
+++ start [2023/09/24 13:55] – [September] anderson
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 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| 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 1:\\  Aug 22, 24   | Course overview. Jupyter notebooks.    | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/01 Introduction to CS545.ipynb|01 Introduction to CS545]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/02 Searching for Good Weights in a Linear Model.ipynb|02 Searching for Good Weights in a Linear Model]]  | [[https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html|JupyterLab Introduction]], watch the video then play with jupyter lab.  \\ [[https://tinyurl.com/2qw45tlp|The Batch]] from DeepLearning.AI. Yay, Colorado!  \\  [[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  | Regression. Introduction to neural networks. Jupyter notebook animations.   | | |
+| Week 2:\\  Aug 29, 31  | Jupyter notebook animations. Optimization algorithms. Simple linear and nonlinear models.   | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/01a Simple Animations.ipynb|01a Simple Animations]] \\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/02 Searching for Good Weights in a Linear Model.ipynb|02 Searching for Good Weights in a Linear Model]] \\  [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/02a Generative AI--Friend or Foe.ipynb|02a Generative AI--Friend or Foe]] \\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/03 Fitting Simple Models Using Gradient Descent in the Squared Error.ipynb|03 Searching for Good Weights in a Linear Model]]  |   |  |
 ===== September =====
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 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 3:\\  Sept 5, 7  | Python clases. Design of NeuralNetwork class.   | | | |
+| Week 3:\\  Sept 5, 7\\ Chuck's office hours Thursday will be from 2 to 3:30.  | Confidence intervals. Introduction to neural networks.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/04 Training Multiple Models to Obtain Confidence Intervals.ipynb|04 Training Multiple Models to Obtain Confidence Intervals]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/05 Introduction to Neural Networks.ipynb|05 Introduction to Neural Networks]] | | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/A1.ipynb|A1]] due Friday, September 8th, 10:00 PM  |
-| Week 4:\\  Sept 12, 14   | Optimizers.  | | |
+| Week 4:\\  Sept 12, 14   | Design of NeuralNetwork class. Optimizers.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/06 Python Classes.ipynb|06 Python Classes]]\\ [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/07 Optimizers.ipynb|07 Optimizers]]   | [[https://machinelearningmastery.com/weight-initialization-for-deep-learning-neural-networks/|Weight Initialization for Deep Learning Neural Networks]], by Jason Brownlee  |
-| Week 5:\\  Sept 19, 21  | Introduction to classification.  | | |
+| Week 5:\\  Sept 19, 21  | Using optimizers.  | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/08 Collecting All Weights into One-Dimensional Vector for Use in Optimizers.ipynb|08 Collecting All Weights into One-Dimensional Vector for Use in Optimizers]]   | | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/A2 NeuralNetwork Class.ipynb|A2 NeuralNetwork Class]] due Thursday, September 21st, 10:00 PM\\ <color red>A2 and A2grader.zip updated Sept. 19, 10:45 AM</color>  |
-| Week 6:\\  Sept 26, 28  | Classification. Convolutional neural networks.  | | |
+| Week 6:\\  Sept 26, 28\\ No on-campus lectures. Thursday lecture live through this [[https://zoom.us/j/98356509028|zoom link]]. Tuesday office hours moved to Wednesday, same time. Office hours sign up still use the form in the course Overview page.  | Early stopping (new version of optimizers). A3. Introduction to classification.   |  [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/07a Optimizers2.ipynb|07a Optimizers2]]\\ Tuesday lecture pre-recorded and available now on Echo360.  |
 ===== October =====
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 ^  Week      ^  Topic      ^  Lecture Notes  ^  Reading          ^  Assignments  ^
-| Week 7:\\  Oct 3, 5  | Introduction to Jax and Pytorch.  | | |
+| Week 7:\\  Oct 3, 5  | Classification. Convolutional Networks.  | | | [[https://nbviewer.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/A3 NeuralNetwork Class Using Optimizers.ipynb|A3 NeuralNetwork Class Using Optimizers]] due Thursday, October 5th, 10:00 PM |
 | Week 8:\\  Oct 10, 12  | More convolutional neural networks.  | | |
 | Week 9:\\  Oct 17, 19  | Introduction to reinforcement leanring. Learning to play games. | | |