Deep Learning important Channels and Courses

# Deep Learning important Channels and Courses --- [toc] --- ## Channels ### General #### Deeplearning ai - https://www.youtube.com/channel/UCcIXc5mJsHVYTZR1maL5l9w/playlists #### Hung-yi Lee - https://www.youtube.com/c/HungyiLeeNTU/playlists #### Hsuan-Tien Lin - https://www.youtube.com/c/hsuantien/playlists #### Yannic Kilcher - https://www.youtube.com/c/YannicKilcher/playlists #### Siraj Raval - https://www.youtube.com/c/SirajRaval/playlists - #### KDD2016 video - https://www.youtube.com/c/KDD2016video/playlists ### Computer Vision(3D) #### sentdex - https://www.youtube.com/c/sentdex/playlists #### Anuj shah - https://www.youtube.com/c/Anujshah_Deep_Learning_Garage/playlists ### Computer Graphics #### Two Minute Papers - https://www.youtube.com/c/K%C3%A1rolyZsolnai/playlists ### Speeches #### Foundations of Deep Learning (Hugo Larochelle, Twitter) - https://youtu.be/zij_FTbJHsk #### Deep Learning for Computer Vision (Andrej Karpathy, OpenAI) - https://youtu.be/u6aEYuemt0M #### Deep Learning for Natural Language Processing (Richard Socher, Salesforce) - https://youtu.be/oGk1v1jQITw #### TensorFlow Tutorial (Sherry Moore, Google Brain) - https://youtu.be/Ejec3ID_h0w #### Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU) - https://youtu.be/rK6bchqeaN8 #### Nuts and Bolts of Applying Deep Learning (Andrew Ng) - https://youtu.be/F1ka6a13S9I #### Deep Reinforcement Learning (John Schulman, OpenAI) - https://youtu.be/PtAIh9KSnjo #### Theano Tutorial (Pascal Lamblin, MILA) - https://youtu.be/OU8I1oJ9HhI #### Deep Learning for Speech Recognition (Adam Coates, Baidu) - https://youtu.be/g-sndkf7mCs #### Torch Tutorial (Alex Wiltschko, Twitter) - https://youtu.be/L1sHcj3qDNc #### Sequence to Sequence Deep Learning (Quoc Le, Google) - https://youtu.be/G5RY_SUJih4 #### Foundations and Challenges of Deep Learning (Yoshua Bengio) - https://youtu.be/11rsu_WwZTc #### 還有 Ian Goodfellow 關於 GAN 的演講: - https://www.youtube.com/watch?v=HN9NRhm9waY --- ## Courses ### Introduction course #### Deep learning ai by Prof. Ng - https://bit.ly/2ESEiJv #### Introduction to Deep Learning by Prof. Raj from CMU - https://bit.ly/2Wpz03d #### Representation Learning by Prof. Courville from MILA - https://bit.ly/2QM2fH6 --- ### Deep Learning Theory #### Topics course Mathematics of Deep Learning by Prof. Bruna from NYU Courant - https://bit.ly/2Z9JUHe #### Science of Deep Learning: Bridging Theory and Practice by Prof. Mądry&Daskalakis from MIT - https://bit.ly/2wEIXKO --- ### Learning Techniques #### CS294-158 Deep Unsupervised Learning by Prof. Abbeel from UC Berkeley - https://bit.ly/2TODPfW #### CS294-112 Deep Reinforcement Learning by Prof. Levine from UC Berkeley - https://bit.ly/2Jde9pN #### CS 236: Deep Generative Models by Prof. Ermon & Grover from Stanford - https://bit.ly/2ZahXPg #### CS 330: Multi-Task and Meta-Learning by Prof. Finn from Stanford - https://reurl.cc/9zO5QV --- ### Computer Vision #### CS 131 Computer Vision: Foundations and Applications by Prof. Fei-Fei Li et al. from Stanford - https://stanford.io/2K4BjC2 #### CS231n: Convolutional Neural Networks for Visual Recognition by Prof. Fei-Fei Li et al. from Stanford - http://cs231n.stanford.edu/ #### Deep Learning for Computer Vision(University of Michigan) - https://web.eecs.umich.edu/~justincj/teaching/eecs498/FA2020/ #### CS391R: Robot Learning (University of texas at Austin) - https://www.cs.utexas.edu/~yukez/cs391r_fall2020/index.html #### ADL4CV - Advanced Deep Learning for Computer Vision - Technical University Munich - Prof. Leal-Taixé and Prof. Niessner (WS20-21) - https://www.youtube.com/playlist?list=PLog3nOPCjKBkngkkF552-Hiwa5t_ZeDnh&fbclid=IwAR1Fy-SLtlqZYP1jycumnG42HNll2omg53vAIE8zr3NV3jEpxlVglgpj9r4 #### CV3DST - Computer Vision 3: Detection, Segmentation and Tracking - Technical University Munich - Prof. Leal-Taixé (SS20) - https://www.youtube.com/playlist?list=PLog3nOPCjKBneGyffEktlXXMfv1OtKmCs&fbclid=IwAR3eFhq-T0etvr3qLU5IPxOKsn8RbFBuJHhwiR0vCNi37yOcFPla-ytEY-g --- ### Natural Language Processing #### CS224n Natural Language Processing with Deep Learning by Prof. Manning from Stanford - https://stanford.io/2lNGlER #### Deep Natural Language Processing by Prof. Blunsom et al. from DeepMind & Oxford - https://bit.ly/2kh4Esz --- ### Network Analysis #### CS224W Analysis of Networks: Mining and Learning with Graphs by Prof. Leskovec from Stanford - https://stanford.io/2KuPSOH --- ### System of Deep (machine) Learning #### System for ML by Dr. Tianqi Chen from the University of Washington - https://bit.ly/2Kwv5KK #### CS217: Hardware Accelerators for Machine Learning by Prof. Olukoton&Pedram from Stanford - https://stanford.io/2IlOJ9B --- ### Deep (machine) learning in Biology/Medicine #### CS273B Deep Learning in Genomics and Biomedicine by Prof. Zhou&Kundaje from Stanford - https://stanford.io/2Ktqtop #### CS897Machine Learning for Healthcare by Prof. Songtag & Szolovits from MIT - https://mlhc19mit.github.io/ --- ## Social Mediaes ### Learning By Hacking - https://www.facebook.com/datasci.info/?ref=page_internal ----