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fa24/interml/calendar.md

@@ -51,7 +51,7 @@ Week | Dates |  Topics | Demos & Tutorials |  Lecture Slides | Readings & Notes
 7 | Oct 7, 9 | Variational inference | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/variational/vae_demo.ipynb) [Variational autoencoders](https://github.com/YData123/sds365-fa22/raw/main/demos/variational/vae_demo.zip) |  Mon: [<span style="color:">Variational inference</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-7.pdf) <br> Wed: [<span style="color:">VAEs</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-9.pdf) <br> | PML Section 20.3 <br> [Notes on variational inference](https://github.com/YData123/sds365-fa24/raw/main/notes/variational.pdf)  | Assn 2 in <br>  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/main/assignments/assn3/assn3.ipynb) [<span style="color:">Assn 3 out</span>](https://github.com/YData123/sds365-fa24/raw/main/assignments/assn3/assn3.zip)
 8 | Oct 14 | Midterm  | | | [<span style="color:">Practice midterms</span>](https://yale.instructure.com/courses/98751/files/folder/Midterm/practice) | Oct 14: Midterm exam
 9 | Oct 21, 23 | Graphs and structure learning | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/graphs/glasso_demo.ipynb) [Graphical lasso demo](https://github.com/YData123/sds365-fa22/raw/main/demos/graphs/glasso_demo.zip) | Mon: [<span style="color:">Sparsity and graphs</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-21.pdf) <br> Wed: [<span style="color:">Discrete data and graph neural nets</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-23.pdf) |  [Notes on graphs and structure learning](https://github.com/YData123/sds365-fa24/raw/main/notes/graphs.pdf)  <br> [Graph neural networks](https://distill.pub/2021/understanding-gnns/) <br> PML Section 23.4 |
-10 | Oct 28, Oct 30 | Deep reinforcement learning | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/q_learning/qlearning_demo.ipynb) [Q-learning demo](https://github.com/YData123/sds365-fa22/raw/main/demos/q_learning/qlearning_demo.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/dqn_demo/dqn_demo.ipynb) [DQN demo](https://github.com/YData123/sds365-fa22/raw/main/demos/dqn_demo/dqn_demo.zip) |  Mon: [<span style="color:gray">Reinforcement learning</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-30.pdf) <br> Wed: [<span style="color:gray">Deep reinforcement learning</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-1.pdf) | Sutton and Barto, Section 6.5 | Oct 30: Assn 3 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/main/assignments/assn4/assn4.ipynb) [<span style="color:gray">Assn 4 out</span>](https://github.com/YData123/sds365-fa24/raw/main/assignments/assn4/assn4.zip)
+10 | Oct 28, Oct 30 | Deep reinforcement learning | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/q_learning/qlearning_demo.ipynb) [Q-learning demo](https://github.com/YData123/sds365-fa22/raw/main/demos/q_learning/qlearning_demo.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/dqn_demo/dqn_demo.ipynb) [DQN demo](https://github.com/YData123/sds365-fa22/raw/main/demos/dqn_demo/dqn_demo.zip) |  Mon: [<span style="color:">Reinforcement learning</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-28.pdf) <br> Wed: [<span style="color:">Deep reinforcement learning</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-oct-30.pdf) | Sutton and Barto, Section 6.5 | Oct 30: Assn 3 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/main/assignments/assn4/assn4.ipynb) [<span style="color:gray">Assn 4 out</span>](https://github.com/YData123/sds365-fa24/raw/main/assignments/assn4/assn4.zip)
 11 | Nov 4, 6 | Policy gradient methods |  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/policy_gradients_demo/policy_gradients_demo.ipynb) [Policy gradients demo](https://github.com/YData123/sds365-fa24/raw/main/demos/policy_gradients_demo/policy_gradients_demo.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/actor_critic/actor_critic_demo.ipynb) [Actor-critic demo](https://github.com/YData123/sds365-fa24/raw/main/demos/actor_critic/actor_critic_demo.zip) | Mon: [<span style="color:gray">Policy gradient methods</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-6.pdf) <br> Wed: [<span style="color:gray">Actor-critic methods</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-8.pdf) | Sutton and Barto, Section 13.1-13.3, 13.5 | [<span style="color:gray">Quiz 4</span>](https://yale.instructure.com/courses/98751/quizzes) 
 12 | Nov 11, 13 | Sequential models | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/rnn_demo/rnn-demo.ipynb) [vanilla RNN](https://github.com/YData123/sds365-fa22/raw/main/demos/rnn_demo/rnn-demo.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/gru_demo/julius_tensor.ipynb) [Fakespeare GRU](https://github.com/YData123/sds365-fa22/raw/main/demos/gru_demo/julius_tensor.zip)  | Mon: [<span style="color:gray">HMMs and RNNs</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-13.pdf) <br> Wed: [<span style="color:gray">RNNs, GRUs, LSTMs, and all that</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-15.pdf)| [TensorFlow: Text generation](https://www.tensorflow.org/text/tutorials/text_generation) <br> [Notes on HMMs and Kalman filters](https://github.com/YData123/sds365-fa24/raw/main/notes/hmm-kalman.pdf) <br> PML Chapter 15 | Assn 4 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/main/assignments/assn5/assn5.ipynb) [<span style="color:gray">Assn 5 out</span>](https://github.com/YData123/sds365-fa24/raw/main/assignments/assn5/assn5.zip)
 13 | Nov 18, 20 | Sequence-to-sequence models and Transformers |  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/main/demos/gpt-4/hello_gpt4.ipynb) [GPT-4 Python API](https://github.com/YData123/sds365-fa24/raw/main/demos/gpt-4/hello_gpt4.zip) <!--<br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds365-fa24/blob/master/demos/gpt-3/hello_codex.ipynb) [Codex demo](https://github.com/YData123/sds365-fa22/raw/main/demos/gpt-3/hello_codex.zip)--> |  Mon: [<span style="color:gray">Sequence-to-sequence models</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-27.pdf) <br> Wed: [<span style="color:gray">Attention and transformers</span>](https://github.com/YData123/sds365-fa24/raw/main/lectures/lecture-nov-29.pdf) | [Notes on mixtures](https://github.com/YData123/sds365-fa24/raw/main/notes/mixtures.pdf) <br> PML Sections 15.4, 15.5 | [<span style="color:gray">Quiz 5</span>](https://yale.instructure.com/courses/98751/quizzes)