| 1 |
3 Jan |
Introduction and Logistics [Slides] |
| None |
4 Jan |
Pre-requisites quiz released |
| 2 |
5 Jan |
Convention, Metrics, Classification, Regression [Slides] |
| 3 |
10 Jan |
Decision Trees - 1[Slides][Notebook] |
| 4 |
12 Jan |
Decision Trees - 2[Slides][Notebook] |
| 5 |
17 Jan |
Bias and Variance[Slides][Notebook on Python utils][Notebook on Grid Search] |
| None |
18 Jan |
Quiz 1 |
| 6 |
19 Jan |
Bias, Variance 2, Cross Validation[Slides] |
| 7 |
24 Jan |
Ensemble Methods[Slides] |
| 8 |
31 Jan |
Ensemble Methods[Slides], Weighted samples in decision trees[Slides], Maths for ML-1 [Slides] [Notebook-1] [Notebook 2], [Streamlit app] Linear Regression [Slides] |
| 9 |
2 Feb |
Linear Regression [Slides], Contour Plots [Slides], Geometric View of Linear Regression [Slides] |
| 10 |
9 Feb |
Linear Regression II [Slides] |
| 11 |
14 Feb |
Gradient Descent [Slides], Taylor’s Series, Notebook on Taylor’s series, Reference on relationship between Taylor’s series and GD, Reference 2 |
| 12 |
16 Feb |
Gradient Descent [Slides] Notebook |
| 13 |
21 Feb |
Gradient Descent continued, [Ridge Regression], [Streamlit demo], [Additional reading on SGD being an unbiased estimator] |
| 14 |
23 Feb |
Ridge regression, LASSO, [Interactive article on Optimization algorithms] |
| 15 |
28 Feb |
Logistic regression [Slides], [Notebook] (best run locally to render interactive visualisations) |
| 16 |
2 Mar |
Logistic regression [Slides] |
| 17 |
14 Mar |
Logistic regression [Slides] |
| 18 |
16 Mar |
MLP [Slides] |
| 19 |
21 Mar |
MLP [Slides], Notebook |
| 20 |
28 Mar |
MLP [Slides] |
| 21 |
30 Mar |
Next work prediction [Slides], Notebook |
| 22 |
4 Apr |
Convolutional Neural Networks [Slides], 1d CNN slides, Notebook 1, Notebook 2, Notebook 3, Equivariance v/s Invariance, Reference1, Reference2, Notebook |
| 23 |
6 Apr |
Autograd [Slides], Notebook on Autodiff, Reference on chain rule Naive Bayes [Slides] |
| 24 |
11 Apr |
Naive Bayes [Slides], KNN [Slides] |
| 25 |
13 Apr |
KNN, Parametric v/s Non-Parametric, Movie Recommendation |
| 26 |
18 Apr |
Curse of Dimensionality, Segment Anything demo, Unsupervised learning, Image segmentation, Image completion, KMeans Viz 1, Viz 2, PCA reference |
| 27 |
20 Apr |
Constrained Optimization (self study), Support Vector Machines -1 |
| 28 |
23 Apr |
Support Vector Machines |
| 29 |
25 Apr |
Support Vector Machines (Soft Margin) |