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Add some Generative AI, ML courses (#381)
* Add MIT 6.S184 (2025) * Add Johns Hopkins Unsupervised Learning (SP17)
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- #### **Generative AI**
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- [Stanford CS236: Deep Generative Models I 2023 I Stefano Ermon](https://www.youtube.com/playlist?list=PLoROMvodv4rPOWA-omMM6STXaWW4FvJT8)
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- [CS 6785 - Deep Generative Models - Cornell Tech, Spring 2023)](https://www.youtube.com/playlist?list=PL2UML_KCiC0UPzjW9BjO-IW6dqliu9O4B)
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- [MIT 6.S184 Flow Matching and Diffusion Models, 2025](https://diffusion.csail.mit.edu)
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- #### **Computer Vision**
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- [CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University](https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)
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- [ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming](https://www.youtube.com/playlist?list=PLcByDTr7vRTYJ2s6DL-3bzjGwtQif33y3)
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- [EE512A - Advanced Inference in Graphical Models, Fall Quarter, 2014](https://people.ece.uw.edu/bilmes/classes/ee512/ee512_fall_2014/)
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- [UIUC STAT 437 Unsupervised Learning spring 2024, by Tori Ellison](https://www.youtube.com/playlist?list=PLIygTcviGPKB133Vh7zxsxFoblyfS4P5Y)
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- [Johns Hopkins Unsupervised Learning spring 2017, by Rene Vidal](https://www.youtube.com/playlist?list=PLaBAmmD3yH4Nta9Y6g9hOV4dcnpTzeW4q)
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- [University of Wisconsin-Madison CS/ECE 561 - Probability and Information Theory in Machine Learning fall 2020, by Matthew Malley](https://mediaspace.wisc.edu/channel/CS_ECE%2B561%2B-%2BProbability%2Band%2BInfo%2BTheory%2Bin%2BMachine%2BLearning/191748913)
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- [University of Maryland CMSC828U Algorithms in Machine Learning: Guarantees and Analyses fall 2020, by Furong Huang](https://www.cs.umd.edu/class/fall2020/cmsc828u//schedule/) ([YouTube playlist](https://www.youtube.com/playlist?list=PLM0SC1uXFSPo5TO_UN7fia1luj73yuHEC))
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- [Statistical Physics of Machine Learning](https://www.youtube.com/playlist?list=PL04QVxpjcnjgzMr9ehyZUSkwu0Wr0cF_N)
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