This course on Recurrent Neural Networks aims to teach students about sequence modeling, RNN intuition, unfolding RNNs, backpropagation through time, LSTM, RNN applications, and attention mechanisms. The teaching method includes lectures with slides and lab materials. The course is intended for individuals interested in deep learning and neural networks.
MIT 6.S191 - Recurrent Neural Networks
Alexander Amini and Massachusetts Institute of Technology via YouTube
Overview
Syllabus
- Introduction
- Sequence modeling
- Recurrent neural networks
- RNN intuition
- Unfolding RNNs
- Backpropagation through time
- Gradient issues
- Long short term memory LSTM
- RNN applications
- Attention
- Summary
Taught by
https://www.youtube.com/@AAmini/videos
