Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 - Interpretability of Neural Network Published 2019-04-03 Download video MP4 360p Download video MP4 720p Recommendations 1:04:48 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers 28:22 Geoffrey Hinton: The Foundations of Deep Learning 52:28 Mathematics Gives You Wings 48:52 MIT 6.S191: Evidential Deep Learning and Uncertainty 31:51 MAMBA from Scratch: Neural Nets Better and Faster than Transformers 57:33 MIT 6.S191 (2023): Reinforcement Learning 45:46 Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuition 47:27 Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering 1:08:06 Deep Learning Basics: Introduction and Overview 1:13:09 Lecture 10 | Recurrent Neural Networks 1:05:54 Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction - Emma Brunskill 18:08 Transformer Neural Networks Derived from Scratch 1:43:03 Cosmology | Lecture 1 26:46 Andrew Ng: Advice on Getting Started in Deep Learning | AI Podcast Clips 1:58:15 Special Relativity | Lecture 1 57:57 Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition 1:11:36 Geoffrey Hinton talk "What is wrong with convolutional neural nets ?" 59:52 MIT 6.S191 (2023): Deep Generative Modeling 1:08:25 Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 6 – Language Models and RNNs 53:14 MIT 6.S094: Computer Vision Similar videos 1:18:17 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 3 - Full-Cycle Deep Learning Projects 1:26:18 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 5 - AI + Healthcare 1:22:47 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 2 - Deep Learning Intuition 50:24 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 6 - Deep Learning Project Strategy 1:23:00 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 4 - Adversarial Attacks / GANs 1:20:20 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 9 - Deep Reinforcement Learning 1:16:38 Lecture 12 - Backprop & Improving Neural Networks | Stanford CS229: Machine Learning (Autumn 2018) 1:15:56 Introduction to Deep Learning Lecture 7 54:52 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 10 - Chatbots / Closing Remarks 51:02 MedAI #34: Optimizing for Interpretability in Deep Neural Networks | Mike Wu 1:13:23 Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 7 – Vanishing Gradients, Fancy RNNs 1:22:15 Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 4 – Backpropagation 1:02:04 Understanding Deep Neural Networks: From Generalization to Interpretability - Gitta Kutyniok 1:30:01 [NUS CS 6101 - Deep Learning for Vision] - Lecture 7 40:59 Chris Olah - Looking Inside Neural Networks with Mechanistic Interpretability 1:26:56 Interpretable Deep Learning - Deep Learning in Life Sciences - Lecture 05 (Spring 2021) 1:05:41 Interpretable Neural Networks for Computer Vision: Clinical Decisions | AI FOR GOOD DISCOVERY 09:18 JSM Tutorial 2020 - Interpretable Neural Networks More results