Unsupervised Learning Courses and Certifications

Andreas Geiger

Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis

Explores unsupervised learning for 3D-controllable image synthesis, disentangling latent factors like viewpoint and object pose from raw images to create novel, consistent scenes.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Andreas Geiger

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Explore unsupervised disentanglement of factors in natural videos using SlowVAE. Learn about temporal sparse coding, identifiability proof, and performance on benchmark datasets including new natural dynamics benchmarks.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Serrano.Academy

Unsupervised Learning

Explore key unsupervised learning techniques including clustering, dimensionality reduction, and generative models. Gain insights into real-world applications like recommendation systems and image compression.

• YouTube
• 4 hours 30 minutes
• On-Demand
• Free Video

Simons Institute

Power of Active Sampling for Unsupervised Learning

Explore active sampling techniques for unsupervised learning, focusing on matrix completion, graphical models, and clustering. Learn about statistical tradeoffs and computational complexity.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Institute for Advanced Study

Nonlinear Independent Component Analysis - Aapo Hyvärinen

Explore nonlinear independent component analysis, its applications in AI and unsupervised learning, and recent advancements in deep latent variable models with Aapo Hyvärinen.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Shashank Kalanithi

Hands on Machine Learning - Unsupervised Learning

Explore unsupervised learning techniques including clustering, dimensionality reduction, and Gaussian mixture models. Hands-on implementation using Python libraries for data analysis and visualization.

• YouTube
• 58 minutes
• On-Demand
• Free Video

MITCBMM

Unsupervised Learning of Spoken Language with Visual Context

Explores unsupervised learning of spoken language using visual context, aiming to develop ASR capabilities for more languages through audio-visual embedding and clustering techniques.

• YouTube
• 34 minutes
• On-Demand
• Free Video

Aladdin Persson

Latent Dirichlet Allocation with Gibbs Sampling Explained

Comprehensive explanation of Latent Dirichlet Allocation (LDA) with Gibbs Sampling, covering topic modeling, posterior inference, and implementation details. Ideal for those interested in understanding this classic machine learning technique.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Yannic Kilcher

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

Explores challenges in unsupervised learning of disentangled representations, questioning assumptions and efficacy of current approaches through theoretical analysis and extensive experiments.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Yannic Kilcher

Learning to Classify Images Without Labels - Paper Explained

Explore innovative techniques for unsupervised image classification, combining representation learning, clustering, and self-labeling to group visually similar images without predefined labels.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Chemometrics & Machine Learning in Copenhagen

Generalized Tensor Decomposition - Utility for Data Analysis

Explore tensor decomposition methods beyond sum of squares error, including KL divergence and logistic odds, for improved data analysis in various fields like criminology and neuroscience.

• YouTube
• 57 minutes
• On-Demand
• Free Video

International Centre for Theoretical Sciences

Unsupervised ML - Clustering, Dimensionality Reduction, Applications by Rahul Siddharthan

Explore unsupervised machine learning techniques for clustering and dimensionality reduction, with practical applications in data analysis and pattern discovery.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Automated Structure Discovery: Unsupervised Learning: Wolfram U Class

Explore unsupervised machine learning with Wolfram Language, including clustering, feature extraction, and data visualization techniques for automatic structure discovery.

• Wolfram U
• 30 minutes
• On-Demand
• Free Online Course

K-Means Clustering 101: World Happiness Report

16 ratings at Coursera

Explore K-means clustering to analyze global happiness data, grouping countries based on economic, social, and well-being factors for insights into worldwide happiness trends.

• Coursera
• 1 hour 35 minutes
• On-Demand
• Paid Course

AI TIME：无监督学习的公平性研究

Explore cutting-edge fairness concepts in unsupervised learning algorithms, focusing on bias detection, ethical considerations, and practical implementation strategies.

• XuetangX
• On-Demand
• Free Online Course