From a1972c030be2aa427568042417112a100236a445 Mon Sep 17 00:00:00 2001 From: John Lafferty Date: Thu, 24 Oct 2024 09:22:14 -0400 Subject: [PATCH] m --- fa24/introml/calendar.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fa24/introml/calendar.md b/fa24/introml/calendar.md index 26074871..08c68b28 100644 --- a/fa24/introml/calendar.md +++ b/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
principal components | [](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)
[Visualizing trees](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)
[](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: [Trees (and Forests)](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-1.pdf)
Thu: [Forests and PCA](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-3.pdf) | ISL Sections 8.1, 8.2
ISL Section 12.2 | Assn 2 in
[](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn3/assn3.ipynb) [Assn 3 out](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn3/assn3.zip)
| 7 | Oct 8, 10 | PCA and dimension reduction | [](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)
[](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)
[](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: [PCA and word embeddings](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-8.pdf)
Thu: [Embeddings and review](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-10.pdf) | ISL Section 12.2 | [Quiz 3](https://yale.instructure.com/courses/98741/quizzes) 8 | Oct 15 | Midterm exam (in class) | | | On Canvas:
[Practice midterms](https://yale.instructure.com/courses/98741/files/folder/practice_midterms) / [Sample solns](https://yale.instructure.com/courses/98741/files/folder/practice_midterms/)
[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 | [](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)
[](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: [Language models](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-22.pdf)
Thu: [Bayesian inference](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-24.pdf) | [OpenAI: Better language models](https://openai.com/blog/better-language-models/)
[Notes on Bayesian inference](https://github.com/YData123/sds265-fa22/raw/master/notes/bayes-notes.pdf) | Assn 3 in
[](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn4/assn4.ipynb) [Assn 4 out](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn4/assn4.zip) +9 | Oct 22, 24 | Language models, Bayes, topic models | [](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)
[](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: [Language models](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-22.pdf)
Thu: [Bayesian inference](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-24.pdf) | [OpenAI: Better language models](https://openai.com/blog/better-language-models/)
[Notes on Bayesian inference](https://github.com/YData123/sds265-fa22/raw/master/notes/bayes-notes.pdf) | Assn 3 in
[](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn4/assn4.ipynb) [Assn 4 out](https://github.com/YData123/sds265-fa24/raw/main/assignments/assn4/assn4.zip) 10 | Oct 29, Nov 1 | Topic models, introduction to neural networks | [](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)
[](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)
[](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: [ Topic models](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-oct-31.pdf)
Thu: [Neural networks](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-2.pdf) | ISL Sections 10.1, 10.2 | [Quiz 4](https://yale.instructure.com/courses/98741/quizzes) 11 | Nov 5, 7 | Neural networks, reinforcement learning | [](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: [Neural networks](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-7.pdf)
Thu: [Reinforcement learning](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
[](https://colab.research.google.com/github/YData123/sds265-fa24/blob/main/assignments/assn5/assn5.ipynb) [Assn 5 out](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/)
[](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: [ Deep reinforcement learning](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-14.pdf)
Thu: [Deep networks and autoencoders](https://github.com/YData123/sds265-fa24/raw/main/lectures/lecture-nov-16.pdf) | ISL Section 10.7 | [Quiz 5](https://yale.instructure.com/courses/98741/quizzes)