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Andrew Ng with Geoffrey Hinton : Backpropagation & other Deep Learning Phenomena
Lecture 7B : Training RNNs with backpropagation
Lecture 13.1 — The ups and downs of backpropagation — [ Deep Learning | Geoffrey Hinton | UofT ]
Lecture 7.5 — Long term Short term memory — [ Deep Learning | Geoffrey Hinton | UofT ]
Lecture 7.1 — Modeling sequences a brief overview — [ Deep Learning | Geoffrey Hinton | UofT ]
Lecture 7.4 — Why it is difficult to train an RNN — [ Deep Learning | Geoffrey Hinton | UofT ]
Lecture 3.5 — Using the derivatives from backpropagation — [ Deep Learning | Hinton | UofT ]
Lecture 1.3 — Some simple models of neurons — [ Deep Learning | Geoffrey Hinton | UofT ]
Lecture 10.4 — Making full Bayesian learning practical — [ Deep Learning | Geoffrey Hinton | UofT ]
Backpropagation, intuitively | Deep Learning Chapter 3
Geoffrey Hinton: Some Applications of Deep Learning
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Last Updated: October 3, 2026
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Stay Connected! Get the latest insights on Artificial Intelligence (AI) , Natural Language Processing (NLP) , and Large ... This video is a part of the coursera course 'Neural Network and
Lecture 7 2 %e2%80%94 Training Rnns With Back Propagation %e2%80%94 Deep Learning Geoffrey Hinton Uoft.pdf
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![Information Lecture 7.2 — Training RNNs with back propagation — [ Deep Learning | Geoffrey Hinton | UofT ] Guide](https://i.ytimg.com/vi/4gOdNtVNZtk/mqdefault.jpg)
![Full Lecture 7.2 — Training RNNs with back propagation [Neural Networks for Machine Learning] Guide](https://i.ytimg.com/vi/hTcm8AJjvfE/mqdefault.jpg)
![Details Lecture 3.4 — The backpropagation algorithm — [ Deep Learning | Geoffrey Hinton | UofT ] Update](https://i.ytimg.com/vi/VCT1N0EsGj0/mqdefault.jpg)
![Lecture 13.1 — The ups and downs of backpropagation — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/lDFY8vQe6-g/mqdefault.jpg)
![Lecture 7.5 — Long term Short term memory — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/OtFAECd_IXQ/mqdefault.jpg)
![Lecture 7.1 — Modeling sequences a brief overview — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/V0-2pV8vQ84/mqdefault.jpg)
![Lecture 7.4 — Why it is difficult to train an RNN — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/WCngMib2mb4/mqdefault.jpg)
![Lecture 3.5 — Using the derivatives from backpropagation — [ Deep Learning | Hinton | UofT ]](https://i.ytimg.com/vi/7UknKXkcbZA/mqdefault.jpg)
![Lecture 1.3 — Some simple models of neurons — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/VA9niXgGOsQ/mqdefault.jpg)
![Lecture 10.4 — Making full Bayesian learning practical — [ Deep Learning | Geoffrey Hinton | UofT ]](https://i.ytimg.com/vi/RsC9xfHYYH0/mqdefault.jpg)
