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Convolutional Neural Networks Explained Easily

Valerio Velardo - The Sound of AI via YouTube

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Overview

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This course explains the theory and architecture of convolutional neural networks, covering convolution, pooling, and architectural decisions. It also shows how to prepare MFCCs and apply CNNs to audio data.

Syllabus

Intro
Intuition
CNN components
Convolution: Zero padding
Architectural decisions for convolution
Grid size
Depth
# of kernels
Pooling settings
Max pooling (2x2, stride 2)
CNN architecture
How does convolution/pooling apply to audio?
Preparing MFCCs for a CNN
What's up next?

Taught by

Valerio Velardo - The Sound of AI

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