YoVDO

Unsupervised Learning

Offered By: Serrano.Academy via YouTube

Tags

Unsupervised Learning Courses Matrix Factorization Courses Clustering Courses Principal Component Analysis Courses Autoencoders Courses Singular Value Decomposition Courses Restricted Boltzmann Machine Courses Latent Dirichlet Allocation Courses Gaussian Mixture Models Courses

Course Description

Overview

Dive into the world of unsupervised learning through a comprehensive 4.5-hour tutorial covering a wide range of advanced topics. Explore Gaussian Mixture Models, clustering techniques like K-means and Hierarchical clustering, and Principal Component Analysis (PCA). Discover the inner workings of recommendation systems using Matrix Factorization, and delve into Latent Dirichlet Allocation with a two-part explanation including Gibbs Sampling. Gain insights into Restricted Boltzmann Machines, learn about Singular Value Decomposition and its application in image compression, and understand Denoising and Variational Autoencoders. Conclude with a friendly introduction to Generative Adversarial Networks (GANs), equipping yourself with cutting-edge knowledge in unsupervised learning techniques.

Syllabus

Gaussian Mixture Models.
Clustering: K-means and Hierarchical.
Principal Component Analysis (PCA).
How does Netflix recommend movies? Matrix Factorization.
Latent Dirichlet Allocation (Part 1 of 2).
Training Latent Dirichlet Allocation: Gibbs Sampling (Part 2 of 2).
Restricted Boltzmann Machines (RBM) - A friendly introduction.
Singular Value Decomposition (SVD) and Image Compression.
Denoising and Variational Autoencoders.
A Friendly Introduction to Generative Adversarial Networks (GANs).


Taught by

Serrano.Academy

Related Courses

Numerical Linear Algebra
Indian Institute of Technology Roorkee via Swayam
Matrix Methods
University of Minnesota via Coursera
Advanced Recommender Systems
EIT Digital via Coursera
Matrix Computation and its Applications
Indian Institute of Technology Delhi via Swayam
Applied Linear Algebra
NPTEL via YouTube