Gaussian Mixture Models Courses and Certifications

Steve Brunton

Density Estimation with Gaussian Mixture Models and Empirical Priors

Discover advanced density estimation techniques using Gaussian Mixture Models and empirical priors for complex data distributions in this machine learning foundation.

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

Center for Language & Speech Processing(CLSP), JHU

Time Independent ICA through a Fisher Game

Explore Extreme Physical Information theory and its application to Independent Component Analysis through a Fisher game framework. Learn about quantum mechanical connections and data reconstruction techniques.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

UofU Data Science

Mixture of Gaussians and Mean Shift Clustering - Lecture 24

Dive into advanced clustering techniques, exploring Gaussian mixtures, EM algorithms, and Mean Shift methods for sophisticated data analysis and pattern recognition.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Paul G. Allen School

Global Convergence of Over-Parameterized Gradient EM for Learning Gaussian Mixtures

Discover how over-parameterized gradient EM algorithms achieve global convergence when learning Gaussian mixture models through advanced theoretical analysis and practical insights.

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

NPTEL-NOC IITM

Principal Component Analysis (PCA) and Gaussian Mixture Models (GMM) Tutorial

Explore practical applications of PCA for dimensional reduction and GMM clustering on public datasets, including Silhouette Score calculation techniques.

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

HUJI Machine Learning Club

Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models

Delve into high-dimensional mean estimation in binary Markov Gaussian mixture models, exploring how memory in data affects estimation error and the interplay between sample size, dimension, and signal strength.

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

Cluster Analysis and Unsupervised Machine Learning in Python

5235 ratings at Udemy

Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.

• Udemy
• 7 hours 57 minutes
• On-Demand
• Paid Course

Speaker Recognition | By Award Winning Textbook Author

298 ratings at Udemy

Audio processing, feature extraction, speaker recognition, machine learning, and neural networks with coding examples

• Udemy
• 7 hours 54 minutes
• On-Demand
• Paid Course

Motion Detection using Python and OpenCV

63 ratings at Udemy

Implement a vehicle counter and a social distancing detector using background subtraction algorithms! All step by step

• Udemy
• 5 hours 11 minutes
• On-Demand
• Paid Course

Packt

Cluster Analysis and Unsupervised Machine Learning in Python

Master clustering algorithms and unsupervised machine learning techniques in Python, from K-Means to Gaussian Mixture Models, with hands-on implementation and real-world applications.

• Coursera
• 13 hours 39 minutes
• On-Demand
• Paid Course

Institute for Pure & Applied Mathematics (IPAM)

Learning Diagonal Gaussian Mixture Models and Incomplete Tensor Decompositions

Explore parameter learning in diagonal Gaussian mixture models through incomplete symmetric tensor decompositions, with applications in tensor approximation and stability analysis.

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

Complete Your First Project in R

27 ratings at LinkedIn Learning

This course will provide a life-like application R programmers can utilize to enhance their learning along with providing them a project they can add to their coding portfolios.

• LinkedIn Learning
• 2 hours 15 minutes
• On-Demand
• Free Trial Available

Can Diffusion Model Disentangle? A Theoretical Perspective

Explore a theoretical framework for understanding how diffusion models learn disentangled representations, with identifiability conditions, training dynamics analysis, and experimental validation across diverse tasks and modalities.

• YouTube
• 22 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

Alfredo Canziani

PCA, AE, K-Means, Gaussian Mixture Model, Sparse Coding, and Intuitive VAE

Explore advanced machine learning techniques including PCA, autoencoders, K-means, Gaussian mixture models, sparse coding, and VAEs. Gain insights into their applications and intuitive interpretations.

• YouTube
• 1 hour 54 minutes
• On-Demand
• Free Video