CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 Published 2016-01-13 Download video MP4 360p Recommendations 1:18:38 CS231n Winter 2016: Lecture 5: Neural Networks Part 2 09:27 Part 17: AZ 104 Exam Practice Questions | Azure Administrator | Download PDF | #az104examquestions 40:08 The Most Important Algorithm in Machine Learning 16:45 The Clever Way to Count Tanks - Numberphile 12:45 Day in the life of Andrej Karpathy | Lex Fridman Podcast Clips 58:12 MIT Introduction to Deep Learning | 6.S191 17:38 The moment we stopped understanding AI [AlexNet] 15:50 Как пронести несгибаемую трубу максимальной длины по коридорам? 34:32 Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning] 20:18 Why Does Diffusion Work Better than Auto-Regression? 13:49 Andrej Karpathy and Software 2.0 | Chris Lattner and Lex Fridman 10:01 AI, Machine Learning, Deep Learning and Generative AI Explained 31:28 Building a neural network FROM SCRATCH (no Tensorflow/Pytorch, just numpy & math) 1:01:28 How convolutional neural networks work, in depth 25:28 Watching Neural Networks Learn 57:28 CS231n Winter 2016: Lecture 2: Data-driven approach, kNN, Linear Classification 1 18:40 But what is a neural network? | Chapter 1, Deep learning 17:00 Residual Networks and Skip Connections (DL 15) Similar videos 1:19:39 CS231n Winter 2016 Lecture 4 Backpropagation, Neural Networks 1-Q_UWHTY_TEQ.mp4 1:19:01 CS231n Winter 2016: Lecture 7: Convolutional Neural Networks 1:11:43 Deep Learning Lecture 6 (170921) - cs231n Lecture 4: Backpropagation and Neural Networks 1:19:08 CS231n Winter 2016: Lecture1: Introduction and Historical Context 1:09:54 CS231n Winter 2016: Lecture 10: Recurrent Neural Networks, Image Captioning, LSTM 1:18:20 CS231n Winter 2016: Lecture 9: Visualization, Deep Dream, Neural Style, Adversarial Examples 1:19:01 CS231n Winter 2016 Lecture 7 Convolutional Neural Networks LxfUGhug iQ-sHyIqu_S5Ks.mp4 1:11:23 CS231n Winter 2016: Lecture 3: Linear Classification 2, Optimization 1:04:57 CS231n Winter 2016: Lecture 8: Localization and Detection 1:14:50 CS231n Winter 2016: Lecture 15: Invited Talk by Jeff Dean 1:16:07 Lecture 4. Neural Networks and Backpropagation 1:09:36 CS231n Winter 2016 Lecture 6 Neural Networks Part 3 Intro to ConvNets hd-egPTd9zZzec 1:15:03 CS231n Winter 2016: Lecture 11: ConvNets in practice 42:35 Lecture 3/16 : The backpropagation learning procedure More results