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---
title: "CS2007: Machine Learning Techniques"
---
:::{.callout-note}
This site is still under development.
Feedback/Correction: [Click here!](https://forms.gle/LehGfBWFX3yWFDBH6).
:::
::: column-screen-inset-right
| Week | Topic | Lecture Videos | Lecture Slides | Notes PDF | Tutorial Video | Tutorial Slides | Tutorial Colab |
|:------:|:------|:------:|:------:|:------:|:------:|:------:|:------:|
| [1](./pages/Wk01.html) | Introduction; Unsupervised Learning - Representation learning - PCA | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1cX40p8S055Lgb4gN17cZrbtECVw9luoW?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk01.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=BkesMPmhh_E "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut01.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not01.html "Link")|
| [2](./pages/Wk02.html) | Unsupervised Learning - Representation learning - Kernel PCA | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1XN8dAwY5ecAUz1k4B7jK1tMID4OipEtq?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk02.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=Qs8dVQzu43I "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut02.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not02.html "Link")|
| [3](./pages/Wk03.html) | Unsupervised Learning - Clustering - K-means/Kernel K-means | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1waovre6_zqhNkNU9tDGRKRr2fGCX93vp?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk03.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=_4mnXtczNoc "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut03.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not03.html "Link") |
| [4](./pages/Wk04.html) | Unsupervised Learning - Estimation - Recap of MLE + Bayesian estimation, Gaussian Mixture Model - EM algorithm | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1z_j_pFN4O7e3ikBx-pVInepQ5RSB8TLJ?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk04.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://youtu.be/iC215XRWABA?feature=shared "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut04.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not04.html "Link") |
| [5](./pages/Wk05.html) | Supervised Learning - Regression - Least Squares; Bayesian view | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1lLEIjTr88usGj0kxdCP_bx7pNGIhwO9x?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk05.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=mZbr0r6V6JI "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut05.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not05.html "Link") |
| [6](./pages/Wk06.html) | Supervised Learning - Regression - Ridge/LASSO | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/13Ska_N6SsXd6W2la5LkjDQ54SdvnAfcj?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk06.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=YziPX5i9trQ "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut06.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not06.html "Link") |
| [7](./pages/Wk07.html) | Supervised Learning - Classification - K-NN, Decision tree | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1iLLM9VLvjvMZsHHm1LapURayLIAS74ux?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk07.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](https://www.youtube.com/watch?v=V9oYx-uV9VQ "Link"){aria-label="Lab 0 slides" target="_blank"} | [🖥️](./notes/Tut07.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not07.html "Link") |
| [8](./pages/Wk08.html) | Supervised Learning - Classification - Generative Models - Naive Bayes | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1K7VfgPSTOa3NkbsF68EfTdeJ8sgbuupA?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk08.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | | [🖥️](./notes/Tut08.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not08.html "Link") |
| [9](./pages/Wk09.html) | Discriminative Models - Perceptron; Logistic Regression | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1zQdsNR3tEbCiOT1AFp1BVg0z1VfHuOGz?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk09.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} | | [🖥️](./notes/Tut09.pdf "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](./pages/Not09.html "Link") |
| [10](./pages/Wk10.html) | Support Vector Machines | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1yyCgrBMzVKMOahPYaYyupoqSvBcd3y2S?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} | [📝](./notes/Wk10.pdf "PDF"){aria-label="Lab 0 slides" target="_blank"} |
| [11](./pages/Wk11.html) | Ensemble methods - Bagging and Boosting (Adaboost) | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1edYXB-V0Hx4CFaXyg4LlVduaZUb9R6SB?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} |
| [12](./) | Artificial Neural networks; Multiclass classification | [🖥️](https://www.youtube.com/playlist?list=PLZ2ps__7DhBbA_e6_G3FI-BA1f7lCINUu "Link"){aria-label="Lab 0 slides" target="_blank"} | [🎫](https://drive.google.com/drive/folders/1wMRJXASoTwYMNSpaV3ySViWFl6nd3lea?usp=drive_link "Link"){aria-label="Lab 0 slides" target="_blank"} |
:::