Schedule

Summary
Lecture # Date Topic (Slides) Notebooks YouTube Recording Reading
0 30 Dec 2023 Pre-requisite quiz released
1 3 Jan Introduction and Logistics Transcription and local LLMs, Segmentation and Localization, Prompt to Image Recording
2 5 Jan Convention, Metrics, Classification, Regression Rule based vs ML, Confusion Matrix, Dummy baselines Recording
3 8 Jan Decision Trees 1 Entropy, Decision Trees Real Output, DT Real Input Discrete Output Recording
4 10 Jan Decision Trees 2, Bias and Variance Bias variance, Decision Trees + Overfitting, Underfitting Recording
5 12 Jan Tutorial on Numpy, Pandas, Classes, Cross-validation Numpy, Pandas, Entropy, Classes and Trees, Cross-validation and tuning hyperparameters Tutorial recording, Lecture on Cross-validation
6 15 Jan Cross-validation, Ensemble Methods Cross-validation and tuning hyperparameters Recording
7 17 Jan Lecture on Random Forests , Tutorial on Random Forests + Meshgrid Video Notebook on Random Forests feature importance from scratch, Notebook on meshgrid
8 19 Jan Linear Regression Recording
9 24 Jan Linear Regression: Basis Functions Recording Notebook
10 25 Jan Linear Regression: Geometric Interpretation Recording Notebook
10 27 Jan Multi-colinearity, Dummy Variables Recording Notebook
11 29 Jan Gradient Descent Recording Notebook on Taylor’s series, Notebook on Contour plots and gradient descent
12 31 Jan Tutorial on GCloud + Forecasting + Polynomial Regression with Basis functions Notebook on Polynomial Regression [Repo only - not published], Notebook on Autoregressive Model Article on Polynomial Regression
13 2 Feb Quiz 1
14 5 Feb Gradient Descent Recording Notebook on Gradient Descent
15 7 Feb Movie recommendation, Matrix Factorisation Recording Notebook on Movie Recommendation
16 9 Feb Regularised Linear Regression: Ridge Regression, LASSO Regression Recording
17 12 Feb Coordinate Descent + Time Complexity + ML Maths + Convexity Not Recorded Notebook on Sklearn with GPU [Repo only - not published]
18 14 Feb Mock Quiz [Slides unavailable]
19 16 Feb Guest Lecture by Arjun Bhagoji, Adversarial Examples for ML [Slides unavailable] Notebook [Repo only - not published]   
20 26 Feb Mid sem exam discussion
21 28 Feb Logistic Regression Recording Notebook on why use logits, Notebook on Logistic regression in Torch
22 1 March Logistic Regression Recording Notebook
23 5 March MLP I Recording
24 6 March MLP II Recording Notebook [Repo only - not published]
25 7 March Next token prediction Recording Notebook
26 11 March Mock Quiz [Slides unavailable] Solution [Slides unavailable]
27 13 March Autograd Recording Notebook
28 18 March CNN - I [Slides unavailable], 1D CNN Recording Notebook 1, Notebook 2 on edge detection, Notebook 3 on LeNet
29 20 March CNN - II [Slides unavailable] Recording Notebook [Repo only - not published]
30 22 March KNN Recording Notebook (Parametric v/s Non-Parametric), Notebook (Curse of dimensionality) Reference on Parameteric v/s Non-Parametric from MLSS, ML Mastery, StackExchange, Sebastian Raschka’s blog
31 1 April Reinforcement learning Recording Notebook 1, Notebook 2
32 3 April Unsupervised learning Recording Notebook [Repo only - not published]
33 5 April Approximate KNN Recording Notebook
34 8 April Constrained Optimization 1, Constrained Optimization 2 (self study) Part 2 recording from older run Notebook [Repo only - not published]
35 10 April SVM - I Recording Notebook 1
36 12 April SVM - II (Kernel) Recording Notebook, Notebook 2
37 15 April SVM - III (QP, Kernels as similarity) Recording Notebook on QP, Notebook on kernels-1
38 17 April SVM - IV (Kernel understanding, Soft Margin) Recording Notebook on kernel understanding, Notebook on soft margin
39 19 April Overall revision