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fa24/introml/calendar.md

@@ -53,7 +53,7 @@ Complementary readings marked ISL refer to sections in the book [An Introduction
 6 | Oct 1, 3 | Tree-based methods and <br> principal components | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/trees/trees.ipynb) [Trees and forests](https://github.com/YData123/sds265-fa22/raw/master/demos/trees/trees.zip)  <br> [Visualizing trees](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/pca/pca.ipynb) [PCA examples](https://github.com/YData123/sds265-fa22/raw/master/demos/pca/pca.zip) |   Tue: [<span style="color:">Trees (and Forests)</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-1.pdf) <br> Thu: [<span style="color:">Forests and PCA</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-3.pdf) | ISL Sections 8.1, 8.2 <br> ISL Section 12.2  | Assn 2 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn3/assn3.ipynb) [<span style="color:">Assn 3 out</span>](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn3/assn3.zip) <br>  |
 7 | Oct 8, 10 | PCA and dimension reduction | [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa23/blob/main/demos/pca/pca-demo-redux.ipynb) [PCA revisited](https://github.com/YData123/sds265-fa23/raw/main/demos/pca/pca-demo-redux.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa23/blob/main/demos/pca/iris-pca.ipynb) [Used for dimension reduction](https://github.com/YData123/sds265-fa23/raw/main/demos/pca/iris-pca.zip)  <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/demos/embeddings/embeddings.ipynb) [Word embeddings](https://github.com/YData123/sds265-fa24/raw/main/demos/embeddings/embeddings.zip)| Tue: [<span style="color:">PCA and word embeddings</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-8.pdf) <br> Thu: [<span style="color:">Embeddings and review</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-10.pdf) | ISL Section 12.2 |  [<span style="color:gray">Quiz 3</span>](https://yale.instructure.com/courses/98741/quizzes) 
 8 | Oct 15  |  Midterm exam (in class) |  |   | On Canvas: <br> [Practice midterms](https://yale.instructure.com/courses/98741/files/folder/practice_midterms) / [Sample solns](https://yale.instructure.com/courses/98741/files/folder/practice_midterms/) <br> [Midterm](https://yale.instructure.com/courses/98741/files/folder/midterm/) / [Sample soln](https://yale.instructure.com/courses/98741/files/folder/midterm/)
-9 | Oct 22, 24 | Language models, Bayes, topic models | <!-- [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/language-models/hello_gpt3.ipynb) [GPT-3 demo](https://github.com/YData123/sds265-fa22/raw/master/demos/language-models/hello_gpt3.zip) <br> --> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa23/blob/main/demos/bayes/bayes.ipynb) [Bayesian inference](https://github.com/YData123/sds265-fa23/raw/main/demos/bayes/bayes.zip) <br>[<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/topic-models/topic-models.ipynb) [Topic models](https://github.com/YData123/sds265-fa22/raw/master/demos/topic-mdoels/topic-models.zip) |  Tue: [<span style="color:">Language models</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-22.pdf) <br> Thu: [<span style="color:">Bayesian inference</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-24.pdf) | [OpenAI: Better language models](https://openai.com/blog/better-language-models/) <br> [Notes on Bayesian inference](https://github.com/YData123/sds265-fa22/raw/master/notes/bayes-notes.pdf) <!--<br> <img width="25" src="scream.png">[Notes on simulation](https://github.com/YData123/sds265-fa22/raw/master/notes/simulation.pdf)--> |  Assn 3 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn4/assn4.ipynb) [<span style="color:gray">Assn 4 out</span>](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn4/assn4.zip) 
+9 | Oct 22, 24 | Language models, Bayes, topic models | <!-- [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/language-models/hello_gpt3.ipynb) [GPT-3 demo](https://github.com/YData123/sds265-fa22/raw/master/demos/language-models/hello_gpt3.zip) <br> --> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa23/blob/main/demos/bayes/bayes.ipynb) [Bayesian inference](https://github.com/YData123/sds265-fa23/raw/main/demos/bayes/bayes.zip) <br>[<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/topic-models/topic-models.ipynb) [Topic models](https://github.com/YData123/sds265-fa22/raw/master/demos/topic-mdoels/topic-models.zip) |  Tue: [<span style="color:">Language models</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-22.pdf) <br> Thu: [<span style="color:">Bayesian inference</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-24.pdf) | [OpenAI: Better language models](https://openai.com/blog/better-language-models/) <br> [Notes on Bayesian inference](https://github.com/YData123/sds265-fa22/raw/master/notes/bayes-notes.pdf) <!--<br> <img width="25" src="scream.png">[Notes on simulation](https://github.com/YData123/sds265-fa22/raw/master/notes/simulation.pdf)--> |  Assn 3 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn4/assn4.ipynb) [<span style="color:">Assn 4 out</span>](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn4/assn4.zip) 
 10 | Oct 29, Nov 1 | Topic models, introduction to neural networks |  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/neural-nets/sanity-check.ipynb) [Sanity check](https://github.com/YData123/sds265-fa22/raw/master/demos/neural-nets/sanity-check.zip) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/neural-nets/neural-nets.ipynb) [Minimal neural network](https://github.com/YData123/sds265-fa22/raw/master/demos/neural-nets/neural-nets.zip) <br>  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/neural-nets/neural-nets-regress.ipynb) [Regression examples](https://github.com/YData123/sds265-fa22/raw/master/demos/neural-nets/neural-nets-regress.zip) |  Tue: [<span style="color:gray"> Topic models</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-31.pdf) <br> Thu: [<span style="color:gray">Neural networks</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-2.pdf) |  ISL Sections 10.1, 10.2 |  [<span style="color:gray">Quiz 4</span>](https://yale.instructure.com/courses/98741/quizzes)
 11 | Nov 5, 7 | Neural networks, reinforcement learning |  [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa23/blob/main/demos/reinforcement-learning/reinforcement-learning.ipynb) [Q-learning](https://github.com/YData123/sds265-fa23/raw/main/demos/reinforcement-learning/reinforcement-learning.zip) |    Tue: [<span style="color:gray">Neural networks</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-7.pdf) <br> Thu: [<span style="color:gray">Reinforcement learning</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-9.pdf) | [Notes on backpropagation](https://github.com/YData123/sds265-fa22/raw/master/notes/backprop.pdf) | Assn 4 in <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn5/assn5.ipynb) [<span style="color:gray">Assn 5 out</span>](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn5/assn5.zip) 
 12 | Nov 12, 14 | Deep neural networks |  [Tensorflow playground](https://playground.tensorflow.org/) <br> [<img width="25" src="colab.svg">](https://colab.research.google.com/github/YData123/sds265-fa22/blob/master/demos/deep-nets/deep-nets.ipynb) [Autoencoder examples](https://github.com/YData123/sds265-fa22/raw/master/demos/deep-nets/deep-nets.zip)   |  Tue: [<span style="color:gray"> Deep reinforcement learning</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-14.pdf) <br> Thu: [<span style="color:gray">Deep networks and autoencoders</span>](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-16.pdf) | ISL Section 10.7  | [<span style="color:gray">Quiz 5</span>](https://yale.instructure.com/courses/98741/quizzes)