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https://github.com/jamormoussa/stanford-machine-learning-courses
Stanford machine learning courses
https://github.com/jamormoussa/stanford-machine-learning-courses
Last synced: 9 days ago
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Stanford machine learning courses
- Host: GitHub
- URL: https://github.com/jamormoussa/stanford-machine-learning-courses
- Owner: JamorMoussa
- Created: 2024-04-28T12:49:07.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-09-20T11:09:50.000Z (3 months ago)
- Last Synced: 2024-12-16T04:17:25.570Z (9 days ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 446 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Stansford Machine Learning Courses
## 01. CS231n Winter 2016 - Convolutional Neural Networks for Visual Recognition
| | |
|-|-|
| **Instructor** | [Andrej Karpathy](https://karpathy.ai/)|
| **Website** | [https://cs231n.stanford.edu/2016/](https://cs231n.stanford.edu/2016/) |
| **Youtube Playlist** | [https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC](https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC) |
|**Slides**| [https://cs231n.stanford.edu/slides/2016/](https://cs231n.stanford.edu/slides/2016/)|
| Lecture | Done | Video Title | YouTube Link |
|---------|-----------------------|---------------------------------------------------------------------------|--------------|
| 1 | :white_large_square: | Introduction and Historical Context | [Link](https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=1) |
| 2 | :white_check_mark: | Data-driven approach, kNN, Linear Classification 1 | [Link](https://www.youtube.com/watch?v=3zdVZ7tjSYw&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=2) |
| 3 | :white_check_mark: | Linear Classification 2, Optimization | [Link](https://www.youtube.com/watch?v=7eyZsK6vklU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=3) |
| 4 | :white_large_square: | Backpropagation, Neural Networks 1 | [Link](https://www.youtube.com/watch?v=V3alal_qmO4&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=4) |
| 5 | :white_large_square: | Neural Networks Part 2 | [Link](https://www.youtube.com/watch?v=JE9Oa80CS7g&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=5) |
| 6 | :white_large_square: | Neural Networks Part 3 / Intro to ConvNets | [Link](https://www.youtube.com/watch?v=9WK7PJ2SJxY&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=6) |
| 7 | :white_large_square: | Convolutional Neural Networks | [Link](https://www.youtube.com/watch?v=A2YMgVLkrnk&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=7) |
| 8 | :white_large_square: | Localization and Detection | [Link](https://www.youtube.com/watch?v=0miqm-Q4EcU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=8) |
| 9 | :white_large_square: | Visualization, Deep Dream, Neural Style, Adversarial Examples | [Link](https://www.youtube.com/watch?v=ti-uR5UHcFE&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=9) |
| 10 | :white_large_square: | Recurrent Neural Networks, Image Captioning, LSTM | [Link](https://www.youtube.com/watch?v=TVgjXKTGKeE&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=10) |
| 11 | :white_large_square: | ConvNets in practice | [Link](https://www.youtube.com/watch?v=vWzEUhY0CxA&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=11) |
| 12 | :white_large_square: | Deep Learning libraries | [Link](https://www.youtube.com/watch?v=CP0QFhoSAX8&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=12) |
| 13 | :white_large_square: | Videos and Unsupervised Learning | [Link](https://www.youtube.com/watch?v=n_kLL_F-JDU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=13) |
| 14 | :white_large_square: | Segmentation, soft attention, spatial transformers | [Link](https://www.youtube.com/watch?v=EwzY2nG9bxY&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=14) |
| 15 | :white_large_square: | Invited Talk by Jeff Dean | [Link](https://www.youtube.com/watch?v=K8E9zRMsO9s&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC&index=15) |