Autoencoders

Offered By: Pascal Poupart via YouTube

Course Description

Overview

Explore the fundamentals of autoencoders in this 39-minute lecture, covering key concepts such as compression, linear auto encoders, principal component analysis, deep autoencoders, sparse representations, and denoising techniques. Gain insights into the architecture and applications of these powerful neural network models used for unsupervised learning and dimensionality reduction.

Syllabus

Introduction
Compression
Linear Auto Encoder
Principal Component Analysis
Autoencoders
Deep Autoencoders
Sparse representations
Denoising

Taught by

Pascal Poupart

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