Difference between revisions of "Neural Networks"
From MIPAL
(13 intermediate revisions by one user not shown) | |||
Line 2: | Line 2: | ||
* [https://developer.nvidia.com/deep-learning-courses Nvidia deep learning course (free with exercise)] | * [https://developer.nvidia.com/deep-learning-courses Nvidia deep learning course (free with exercise)] | ||
* [http://deeplearning.net/tutorial/contents.html Deep learning tutorial] | * [http://deeplearning.net/tutorial/contents.html Deep learning tutorial] | ||
+ | * [http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html Hugo Larochelle's Neural Networks course (excellent videos)] | ||
+ | * [http://cs231n.stanford.edu/ Stanford CNN course (Spring 2015)] | ||
+ | * [http://colah.github.io/posts/2015-08-Understanding-LSTMs/ Excellent blog on LSTM] | ||
+ | * [http://incompleteideas.net/book/bookdraft2018mar21.pdf Introduction to Reinforcement Learning (Sutton & Barto Book)] | ||
+ | * [https://lilianweng.github.io/lil-log/2018/04/08/policy-gradient-algorithms.html Excellent blog post on Policy Gradient Algorithms (Lilian Weng)] | ||
+ | * [https://deepgenerativemodels.github.io/ Stanford Course on Deep Generative Models (Fall 2018-2019)] | ||
+ | * [http://jalammar.github.io/about/ Excellent Blog on NLP (Transformers and BERT)] | ||
+ | * [http://snap.stanford.edu/proj/embeddings-www/ Graph Neural Networks] WWW-18 Tutorial | ||
+ | * [https://davidstutz.de/a-short-introduction-to-bayesian-neural-networks/ Introduction to Bayesian Neural Networks] | ||
+ | * [https://rajatvd.github.io/NTK/ Neural Tangent Kernel] | ||
+ | * [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)