Lecture
Dimensionality Reduction: PCA and Autoencoders
Description
This lecture covers the basics of artificial neural networks, including multilayer perceptrons and convolutional neural networks. It then delves into the concept of dimensionality reduction, introducing Principal Component Analysis (PCA) and autoencoders as techniques to compress high-dimensional data while preserving relevant information.
Official source
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