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University of Central Florida

Training Neural Networks for Computer Vision - Part I - Lecture 10

University of Central Florida via YouTube

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This lecture explains how to train convolutional neural networks by minimizing cost with differentiable loss functions, backpropagation, gradient descent, and stochastic gradient descent.

Syllabus

Intro
UCF Network Parameters - recap
Convolution - Intuition
General CNN architecture - recap
Learning phases - recap Images
Network Training - Minimize Cost
General approach
Train CNN with Gradient Descent
Loss Functions
Differentiability
Backpropagation - Chain Rule
Optimization demo
Stochastic Gradient Descent

Taught by

UCF CRCV

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