Hellow guys, Welcome to my website, and you are watching MIT 6.S191 (2023): Recurrent Neural Networks, Transformers, and Attention. and this vIdeo is uploaded by Alexander Amini at 2023-03-17T07:00:10-07:00. We are pramote this video only for entertainment and educational perpose only. So, I hop you like our website.
| Name | MIT 6.S191 (2023): Recurrent Neural Networks, Transformers, and Attention |
| Video Uploader | Video From Alexander Amini |
| Upload Date | This Video Uploaded At 17-03-2023 10:00:10 |
| Video Discription | MIT Introduction to Deep Learning 6.S191: Lecture 2 Recurrent Neural Networks Lecturer: Ava Amini 2023 Edition For all lectures, slides, and lab materials: http://introtodeeplearning.com Lecture Outline 0:00 - Introduction 3:07 - Sequence modeling 5:09 - Neurons with recurrence 12:05 - Recurrent neural networks 13:47 - RNN intuition 15:03 - Unfolding RNNs 18:57 - RNNs from scratch 21:50 - Design criteria for sequential modeling 23:45 - Word prediction example 29:57 - Backpropagation through time 32:25 - Gradient issues 37:03 - Long short term memory (LSTM) 39:50 - RNN applications 44:50 - Attention fundamentals 48:10 - Intuition of attention 50:30 - Attention and search relationship 52:40 - Learning attention with neural networks 58:16 - Scaling attention and applications 1:02:02 - Summary Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!! |
| Category | Science & Technology |
| Tags | deep learning | mit | artificial intelligence | neural networks | machine learning | recurrent neural networks | rnn | what is a rnn | 6s191 | 6.s191 | mit deep learning | ava soleimany | soleimany | alexander amini | amini | lecture 2 | tensorflow | computer vision | sequences | deep mind | openai | basics | introduction | deeplearning | ai | tensorflow tutorial | what is deep learning | deep learning basics | deep learning python | sequence modeling | sequential | long short term memory | lstm |
