Tentative Class Schedule

Slides and additional material can be found here.

Class scribbles from 2021 can be found here.

Lec Date Topic Readings Problem Sheet Scribbles and Slides Recordings Optional Readings
1 26 Aug 2026 Introduction and Logistical Details, Supervised Learning, Generalization, Linear Regression, Least Squares, MSE and RMSE LN Chapter-01, Prince Chapter-01 Problem Sheet 0 Pre-requisites Slides, Slides (Part 2) Not recorded this year. Last year’s recordings are available here. Computing Machinery and Intelligence by Alan Turing, Probability Review, Linear Algebra Review
2 02 Sep 2026 Basis Functions, Polynomial Regression, Overfitting, Train/Validation/Test Splits, Ridge, Lasso, and Gradient Methods LN Chapter-01, LN Chapter-02, Bishop section 1.1, 3.1, HTF section 2.3 Problem Sheet 1 (Linear Regression and Gradient Descent) Slides idem The Saga of Highleyman’s Data by Moritz Hardt and Ben Recht.
3 09 Sep 2026 Finish Gradient Methods, K-Nearest Neighbors, and Introduction to Statistical Learning LN Chapter-02, HTF section 3.4.1, 3.4.2 Problem Sheet 2, Notebook Slides idem Implicit Gradient Regularization, Double Descent
4 16 Sep 2026 Tentative: Classification through ERM, Convex Surrogate Losses, and Logistic Regression LN Chapter-03, Chapter-04, HTF section 2.4, 2.5, Bishop section 3.2     idem  
5 23 Sep 2026 Tentative: Data Preprocessing, Feature Reduction, and the Perceptron       idem  
  24 Sep 2026 [Lab Time] First Quiz [5 pm to 6:30 pm]          
  30 Sep 2026 Federal Holiday - No Class          
6 07 Oct 2026 Tentative: Neural Networks and Backpropagation       idem  
  14 Oct 2026 Fall Break - No Class          
7 21 Oct 2026 Tentative: Maximum-Margin Classification       idem  
8 28 Oct 2026 Tentative: Classification Evaluation and Decision Trees       idem  
9 04 Nov 2026 Tentative: Ensembles and K-Fold Cross-Validation       idem  
  05 Nov 2026 [Lab Time] Second Quiz [5 pm to 6:30 pm]          
10 11 Nov 2026 Tentative: Deep Neural Networks, Convolutional Neural Networks, and Optimization       idem  
11 18 Nov 2026 Tentative: Probabilistic Classification and Parameter Estimation       idem  
12 25 Nov 2026 Tentative: Bayesian Learning and Bayesian Regression       idem  
  26 Nov 2026 [Lab Time] Coding Exam [5 pm to 7 pm]          
13 02 Dec 2026 Tentative: Frontiers, Applications, Review, and Questions       idem  
  Early to mid December 2026 [Date and Time TBD] Final Exam          

Tutorials

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