Explore the revolutionary impact of ResNet on deep learning in this comprehensive 59-minute video lecture. Dive into the history of computer vision, understand the anatomy of convolutional neural networks (CNNs), and discover their limitations. Learn about residual networks, the groundbreaking skip connection, and how to perform image classification using ResNet with code examples. Journey through topics such as translational invariance, classic CNN architectures, and residual blocks. Gain insights into the paper that transformed the field of deep learning and has been cited over 110,000 times. By the end, acquire a solid understanding of pre-CNN computer vision, CNN structure, and the game-changing innovations introduced by ResNet.
Understanding and Visualizing ResNets That Forever Revolutionized Deep Learning - What Is ResNet
Overview
Syllabus
Introduction
Typical neural network
Translational invariance
Convolutional neural network
Classic CNN architectures
Residual blocks and the skip connection
ResNet in action
QnA
Taught by
Data Science Dojo
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