Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Untitled
Graph Chatbot
Related lectures (38)
Unsupervised Learning: Clustering & Dimensionality Reduction
Log in to Mediaspace to watch this video
Introduces unsupervised learning through clustering with K-means and dimensionality reduction using PCA, along with practical examples.
Clustering & Density Estimation
Log in to Mediaspace to watch this video
Covers dimensionality reduction, PCA, clustering techniques, and density estimation methods.
Clustering & Density Estimation
Log in to Mediaspace to watch this video
Covers dimensionality reduction, clustering, and density estimation techniques, including PCA, K-means, GMM, and Mean Shift.
Clustering & Density Estimation
Log in to Mediaspace to watch this video
Covers clustering, PCA, LDA, K-means, GMM, KDE, and Mean Shift algorithms for density estimation and clustering.
Data Representation: PCA
Log in to Mediaspace to watch this video
Covers data representation using PCA for dimensionality reduction, focusing on signal preservation and noise removal.
PCA: Directions of Largest Variance
Log in to Mediaspace to watch this video
Covers PCA, finding directions of largest variance, data dimensionality reduction, and limitations of PCA.
Machine Learning Fundamentals
Log in to Mediaspace to watch this video
Introduces fundamental machine learning concepts, covering regression, classification, dimensionality reduction, and deep generative models.
Unsupervised Learning: Dimensionality Reduction and Clustering
Log in to Mediaspace to watch this video
Covers unsupervised learning, focusing on dimensionality reduction and clustering, explaining how it helps find patterns in data without labels.
Dimensionality Reduction
Log in to Mediaspace to watch this video
Introduces artificial neural networks and explores various dimensionality reduction techniques like PCA, LDA, Kernel PCA, and t-SNE.
PCA: Interactive class
Log in to Mediaspace to watch this video
On PCA includes interactive exercises and emphasizes minimizing information loss.
Dimensionality Reduction: PCA and LDA
Log in to Mediaspace to watch this video
Covers dimensionality reduction techniques like PCA and LDA, clustering methods, density estimation, and data representation.
Deep Generative Models: Part 2
Log in to Mediaspace to watch this video
Explores deep generative models, including mixtures of multinomials, PCA, deep autoencoders, convolutional autoencoders, and GANs.
Decomposition into Line Metrics: Example and Outlook
Log in to Mediaspace to watch this video
Covers the decomposition into line metrics, providing examples and discussing its implications.
Visual Intelligence: Machines and Minds
Log in to Mediaspace to watch this video
Explores visual intelligence, image formation, computer vision, and representation understanding in machines and minds.
Photonic Extreme Learning Machines: Reservoir Computing Techniques
Log in to Mediaspace to watch this video
Covers photonic extreme learning machines and reservoir computing, focusing on their architectures, programming techniques, and applications in optical computing.
Machine Learning for Feature Extraction
Log in to Mediaspace to watch this video
Explores machine learning for feature extraction, 3D vision, and neural networks in mobile robotics.
Managing Columns in Professor Recruitment List
Log in to Mediaspace to watch this video
Explains how to manage columns in a professor recruitment list effectively.
Supervised Learning: Likelihood Maximization
Log in to Mediaspace to watch this video
Covers supervised learning through likelihood maximization to find optimal parameters.
Previous
Page 2 of 2
Next
