Hands-On Evolution of Deep Learning – Geoffrey Hinton’s AI Legacy

Master modern neural networks by recreating the groundbreaking discoveries of Geoffrey Hinton, the visionary whose investigation redefined machine subject and heavy learning. Covering his defining papers, this people straight bridges humanities breakthroughs to readable PyTorch code. This hands connected coding people will springiness you a unified look astatine really today's AI scenery was engineered done 1 pioneer’s vision. This people follows the improvement of heavy learning, from Boltzmann Machines and Backpropagation to Deep Belief Networks, Dropout, Knowledge Distillation, Capsule Networks, the Forward-Forward Algorithm, and t-SNE. Course developed by @programmingoceanacademy https://github.com/MOHAMMEDFAHD/Geoffrey-Hinton-Papers-Replicating-In-Pytorch ❤️ Support for this transmission comes from our friends astatine Scrimba – the coding level that's reinvented interactive learning: https://scrimba.com/freecodecamp Chapters - 0:00:00 welcoming - 0:01:31 Introduction - 0:02:39 Objectives - 0:04:23 Acknowledgement - 0:05:10 Disclaimer - 0:06:03 GitHub repo tour - 0:08:25 A Learning Algorithm for Boltzmann Machine - 1:29:06 Learning representations by back-propagating errors - 3:32:10 Distributed Representations - 4:40:46 Adaptive Mixtures of Local Experts - 6:01:47 The Helmholtz Machine - 7:17:07 The Wake-Sleep Algorithm for Unsupervised Neural Networks - 8:33:43 Stochastic Neighbour Embeddings - 9:32:12 A Fast Learning Algorithm For Deep Belief Networks - 10:50:09 Reducing The Dimensionality Of Data With Neural Networks - 12:21:06 Visualizing Data Using T-SNE - 13:52:30 Deep Boltzmann Machine - 14:49:35 Rectified Linear Units Improve Restricted Boltzmann Machine - 16:44:09 ImageNet Classification With Deep Convolutional Neural Networks - 17:54:12 Dropout: A Simple Way to Prevent Neural Network From Overfitting - 18:41:42 Distilling the Knowledge successful a Neural Network - 20:02:54 Layer Normalization - 22:43:52 Dynamic Routing Between Capsules - 24:36:55 A Simple Framework for Contrastive Learning of Visual Representations - 25:53:31 The Forward-Forward Algorithm: Some Preliminary Investigations - 27:27:17 The Ending 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to codification for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles connected programming: https://freecodecamp.org/news