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 The following schedule is **tentative and is being updated**.
+Please send your suggestions regarding lecture topics to Chuck using [[https://tinyurl.com/2nyfzc36|this Google Docs form]].  Questions regarding assignments should be entered in Canvas discussions.
 ===== August =====
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 |< 100% 18% 20% 22% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 1:\\  Aug 23, 25   | Overview of course. Review of neural networks training and use.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/01 Introduction to CS545.ipynb|01 Introduction to CS545]]\\ [[http://nbviewer.ipython.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.  | <color red>Ungraded</color> [[https://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/Quiz1.ipynb|Quiz 1]] due Friday, August 26, 10:00 PM  |
+| Week 1:\\  Aug 23, 256   | Overview of course. Review of neural networks training and use.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/01 Introduction to CS545.ipynb|01 Introduction to CS545]]\\ [[http://nbviewer.ipython.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!   |   |
-| Week 2:\\  Aug 30, Sept 1  | Regression with neural networks.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/03 Fitting Simple Models Using Gradient Descent in the Squared Error.ipynb|03 Fitting Simple Models Using Gradient Descent in the Squared Error]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/04 Introduction to Neural Networks.ipynb|04 Introduction to Neural Networks]]  |
+| Week 2:\\  Aug 30, Sept 1  | Thursday lecture cancelled. Please watch pre-recorded lecture in Echo360. Quiz1 and A1 questions. Regression with neural networks.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/03 Fitting Simple Models Using Gradient Descent in the Squared Error.ipynb|03 Fitting Simple Models Using Gradient Descent in the Squared Error]]  |  |[[https://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/Quiz1.ipynb|Quiz 1]] due Wednesday, August 31, 10:00 PM, in Canvas  |
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 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 3:\\  Sept 6, 8  | A1 questions. Optimizers. Neural Network class.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/05 Optimizers.ipynb|05 Optimizers]]  |
+| Week 3:\\  Sept 6, 8  | Introduction to Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/04 Introduction to Neural Networks.ipynb|04 Introduction to Neural Networks]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/04a Simple Animations.ipynb|04a Simple Animations]]\\   | [[https://doi.org/10.1016/j.neucom.2022.06.111|Activation functions in deep learning: A comprehensive survey and benchmark]], Neurocomputing, volume 503, 2022, pp. 92-108  |   |
-| Week 4:\\  Sept 13, 15  | A2. Autoencoders. Classification.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/06 Autoencoders.ipynb|06 Autoencoders]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/07 Introduction to Classification.ipynb|07 Introduction to Classification]]  | |  |
+| Week 4:\\  Sept 13, 15\\ <color red>Chuck's office hours on the 13th are canceled.</color>  |  Python classes. Optimizers. A2.    | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/04b Introduction to Python Classes.ipynb|04b Introduction to Python Classes]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/05 Optimizers.ipynb|05 Optimizers]]  | [[https://docs.python.org/3/tutorial/classes.html|Classes Tutorial]]  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/A1 Three-Layer Neural Network.ipynb|A1 Three-Layer Neural Network]] due Monday, Sept 12th, at 10:00 PM\\  <color red>A1grader.tar updated Sept. 12th 2:00 pm</color>  |
-| Week 5:\\  Sept 20, 22  | Classification.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/08 Classification with Linear Logistic Regression.ipynb|08 Classification with Linear Logistic Regression]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/09 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|09 Classification with Nonlinear Logistic Regression Using Neural Networks]]  |
+| Week 5:\\  Sept 20, 22  | Autoencoders. Classification.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/06 Autoencoders.ipynb|06 Autoencoders]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/07 Introduction to Classification.ipynb|07 Introduction to Classification]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/08 Classification with Linear Logistic Regression.ipynb|08 Classification with Linear Logistic Regression]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/09 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|09 Classification with Nonlinear Logistic Regression Using Neural Networks]]  |  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/A2 NeuralNetwork Class.ipynb|A2 NeuralNetwork Class]] due Wednesday, Sept 21st, at 10:00 PM  |
 | Week 6:\\  Sept 27, 29  |   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs545/notebooks/10 JAX.ipynb|10 JAX]]\\ [[https://www.cs.colostate.edu/~anderson/cs545/notebooks/neuralnetworks_app.tar|neuralnetworks_app.tar]]  | [[https://moocaholic.medium.com/jax-a13e83f49897|JAX Ecosystem]]\\ [[https://streamlit.io/|Streamlit]]  | |