Difference between revisions of "Neural Networks"
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* [https://davidstutz.de/a-short-introduction-to-bayesian-neural-networks/ Introduction to Bayesian Neural Networks] | * [https://davidstutz.de/a-short-introduction-to-bayesian-neural-networks/ Introduction to Bayesian Neural Networks] | ||
* [https://rajatvd.github.io/NTK/ Neural Tangent Kernel] | * [https://rajatvd.github.io/NTK/ Neural Tangent Kernel] | ||
| − | * [http://www.cs.umd.edu/class/fall2020/cmsc828W/ | + | * [http://www.cs.umd.edu/class/fall2020/cmsc828W/ Excellent class lectures on theoretical backgrounds of DL from Soheil Feizi@UMD] |
| + | * [http://cs330.stanford.edu/ Deep Multi-Task and Meta Learning] (Stanford CS330, Fall 2021, Chelsea Finn) | ||
| + | * [https://deepgenerativemodels.github.io/ Deep Generative Models] (Stanford CS236, Fall 2021, Stefano Ermon & Yang Song) | ||
Latest revision as of 10:27, 26 May 2023
- Introduction to Neural Computation
- Nvidia deep learning course (free with exercise)
- Deep learning tutorial
- Hugo Larochelle's Neural Networks course (excellent videos)
- Stanford CNN course (Spring 2015)
- Excellent blog on LSTM
- Introduction to Reinforcement Learning (Sutton & Barto Book)
- Excellent blog post on Policy Gradient Algorithms (Lilian Weng)
- Stanford Course on Deep Generative Models (Fall 2018-2019)
- Excellent Blog on NLP (Transformers and BERT)
- Graph Neural Networks WWW-18 Tutorial
- Introduction to Bayesian Neural Networks
- Neural Tangent Kernel
- Excellent class lectures on theoretical backgrounds of DL from Soheil Feizi@UMD
- Deep Multi-Task and Meta Learning (Stanford CS330, Fall 2021, Chelsea Finn)
- Deep Generative Models (Stanford CS236, Fall 2021, Stefano Ermon & Yang Song)
