All supplementary material used by me while TA-ing CS3244: Machine Learning

Overview

CS3244-Tutorial-Material

All supplementary material used by me while TA-ing CS3244: Machine Learning at NUS School of Computing.

What is this?

I teach TG-06, the tutorial that takes place every Monday, 1200-1300 in AY21/22 Semester 1. It is fully online this semester.

This repository contains code, figures, and miscelleaneous items that aid me in teaching my class. The main source of reference should be the lecture notes and tutorial questions created by the CS3244 Professors and Teaching Staff.

Official tutorial solutions will be released at the end of every week.

Contents

Here's a list of what I've covered / I'll be covering in my tutorials:

  • T1W3: k-Nearest Neighbours
  • T2W4: Decision Trees
  • T3W5: Linear Models
  • T4W6: Bias-Variance Tradeoff
  • T5W7:
  • T6W8:
  • T7W9:
  • T8W10:
  • T9W11:
  • T10W12:
  • T11W13:

The slides for all my tutorials can be found here.

I have also added a collection of FAQs asked by my students at the end of class, split by the topics covered in this module. You can find it in questions/. It's a growing list so stay tuned for updates added every week.

Contributions

If there are any issues or suggestions, feel free to raise an Issue or PR. All meaningful contributions welcome!

License

MIT

Owner
Rishabh Anand
CS undergrad + ML Research @ NUS • Open-source Jedi • Writer
Rishabh Anand
DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency

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Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

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Official repository for Hierarchical Opacity Propagation for Image Matting

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