Lecture #7: Gradient Descent | Deep Learning and Neural Networks Published 2020-04-19 Download video MP4 360p Recommendations 12:06 Lecture #8: Derivatives [Part 1] | Derivative from First Principle 15:39 Gradient descent simple explanation|gradient descent machine learning|gradient descent algorithm 25:17 Neural Networks from Scratch - P.3 The Dot Product 20:33 Gradient descent, how neural networks learn | Chapter 2, Deep learning 18:32 Backpropagation Details Pt. 1: Optimizing 3 parameters simultaneously. 15:34 Why Padé Approximations Are Great! | Control Systems in Practice 10:00 Autoencoder Explained - Deep Neural Networks 12:45 Back Propagation in Neural Network with an example 12:51 Singular Value Decomposition (SVD): Mathematical Overview 20:54 AdaBoost, Clearly Explained 06:28 Principal Component Analysis (PCA) 49:06 Python Pandas Tutorial (Part 8): Grouping and Aggregating - Analyzing and Exploring Your Data 09:40 Tensors for Neural Networks, Clearly Explained!!! 17:36 The Discrete Fourier Transform (DFT) 3:46:15 Tutorial on Denoising Diffusion-based Generative Modeling: Foundations and Applications 15:40 What Is Fuzzy Logic? | Fuzzy Logic, Part 1 16:12 Word Embedding and Word2Vec, Clearly Explained!!! Similar videos 01:36 Lecture 7 - Animated Gradient Descent - Deep Learning and Neural Networks 1:15:30 Lecture 7 | Training Neural Networks II 11:29 Mini Batch Gradient Descent (C2W2L01) 12:39 Backpropagation And Gradient Descent In Neural Networks | Neural Network Tutorial | Simplilearn 1:14:52 Lecture 7 - Deep Learning Foundations: Neural Tangent Kernels 53:03 25. Stochastic Gradient Descent 11:40 Neural Networks: Stochastic, mini-batch and batch gradient descent 37:53 Gradient Descent in Neural Networks | Batch vs Stochastics vs Mini Batch Gradient Descent 08:23 Lecture 6.1 — Overview of mini batch gradient descent [Neural Networks for Machine Learning] 1:24:13 DeepMind x UCL | Deep Learning Lectures | 2/12 | Neural Networks Foundations 18:40 But what is a neural network? | Chapter 1, Deep learning 1:34:58 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 - Interpretability of Neural Network 1:13:23 Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 7 – Vanishing Gradients, Fancy RNNs More results