'How neural networks learn' - Part III: Generalization and Overfitting Published 2019-03-10 Download video MP4 360p Recommendations 09:54 Why humans learn so much faster than AI 14:22 How AI Learns Concepts 40:08 The Most Important Algorithm in Machine Learning 15:05 Variational Autoencoders 55:55 Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024) 15:00 'How neural networks learn' - Part I: Feature Visualization 16:27 An introduction to Reinforcement Learning 26:46 Andrew Ng: Advice on Getting Started in Deep Learning | AI Podcast Clips 11:40 Regularization in a Neural Network | Dealing with overfitting 16:01 Reinforcement Learning with sparse rewards 09:09 Neural Network Architectures & Deep Learning 08:49 Batch Normalization - EXPLAINED! 12:14 AlphaGo - How AI mastered the hardest boardgame in history 28:48 LSTM is dead. Long Live Transformers! 17:05 Kolmogorov Arnold Networks (KAN) Paper Explained - An exciting new paradigm for Deep Learning? 1:24:44 Stanford Seminar - Information Theory of Deep Learning, Naftali Tishby Similar videos 04:16 Overfitting in a Neural Network explained 29:47 Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained) 05:45 Neural Network In 5 Minutes | What Is A Neural Network? | How Neural Networks Work | Simplilearn 10:49 Shortcut Learning - A generalization problem in deep neural networks 07:10 Why Does Regularization Reduce Overfitting in Deep Neural Networks? 14:21 LESSON 20: MASTERING MACHINE LEARNING ALGORITHM | Generalization vis-à-vis Overfitting 08:18 Generalization & Overfitting: Intro 25:38 Deep Learning Theory 3-1: Generalization Capability of Deep Learning 13:39 Overfitting and Underfitting in Neural Networks and How To Reduce It 09:43 Deep Neural Network Regularization - Part 1 06:27 Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn More results