Matrix Factorization Courses and Certifications

Institute for Pure & Applied Mathematics (IPAM)

Learning Deep Matrix Factorizations Via Gradient Descent - Implicit Bias Towards Low Rank

Explores implicit bias in gradient descent algorithms for deep matrix factorizations, analyzing convergence to low-rank matrices and discussing implications for tensor decompositions.

• YouTube
• 37 minutes
• On-Demand
• Free Online Course

Fields Institute

Factorization of Completely Positive Matrices Using Iterative Projected Gradient Steps

Explore iterative projected gradient steps for factorizing completely positive matrices in this advanced mathematical lecture from the University of Vienna.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Online Course

A Vision of Linear Algebra

Explore Professor Strang's innovative approach to linear algebra, covering key concepts like column space, eigenvalues, and matrix factorizations through a series of concise, insightful videos.

• MIT OpenCourseWare
• On-Demand
• Free Online Course

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD

1 review

This course takes you through roughly five weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.

• edX
• 3 weeks, 5-6 hours a week
• On-Demand
• Free Online Course (Audit)

Linear Algebra II: Matrix Algebra

8 ratings at edX

This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.

• edX
• 3 weeks, 5-6 hours a week
• On-Demand
• Free Online Course (Audit)

Microcredential

Introductory Linear Algebra

Explore fundamental linear algebra concepts, from systems of equations to matrix algebra, with applications in economics and computer graphics. Develop problem-solving skills for real-world scenarios.

• edX
• 6 weeks, 5-6 hours a week
• On-Demand
• $398.00
• 2 courses

Microcredential

Recommender Systems

Comprehensive exploration of recommender systems, covering fundamental techniques to advanced topics. Gain practical skills through interactive exercises and implement real-world solutions using various algorithms and tools.

• Coursera
• 22 weeks, 3 hours a week
• On-Demand
• Paid Course
• 5 courses

Matrix Factorization and Advanced Techniques

186 ratings at Coursera

Explore matrix factorization and hybrid techniques for recommender systems, covering dimensionality reduction, algorithm combination, and advanced machine learning methods for powerful recommendations.

• Coursera
• 15 hours 51 minutes
• On-Demand
• Free Online Course (Audit)

Recommender Systems and Deep Learning in Python

5605 ratings at Udemy

The most in-depth course on recommendation systems with deep learning, machine learning, data science, and AI techniques

• Udemy
• 12 hours 31 minutes
• On-Demand
• Paid Course

Université de Montréal

Recommender Systems: Behind the Screen

How are items recommended when you’re browsing for movies, jobs or clothing online? Register here and you’ll discover the fundamental concepts and methods allowing the most relevant item suggestions to users from e-commerce to online advertisement.

• edX
• 6 weeks, 4-6 hours a week
• On-Demand
• Free Online Course (Audit)

Université de Montréal

Les coulisses des systèmes de recommandation

Exploration approfondie des systèmes de recommandation, couvrant l'apprentissage automatique, l'évaluation, la modélisation avancée, les bandits contextuels, le classement et l'équité algorithmique.

• edX
• 3 weeks, 29-31 hours a week
• On-Demand
• Free Online Course (Audit)

Alan Turing Institute

Engineering the Future of Medicine - The Turing Lectures

1 review

Explore cutting-edge machine learning applications in biomedical data interpretation, from cellular analysis to surgical skill assessment, with renowned engineer René Vidal.

• YouTube
• 1 hour 27 minutes
• On-Demand
• Free Online Course

Building Recommendation Engines with PySpark

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Building Recommendation Engines in Python

Learn to build recommendation engines in Python using machine learning techniques.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Linear Algebra Basics for Computer Vision - Lecture 2

Explore essential linear algebra concepts including vectors, matrices, transformations, and SVD, with practical applications in computer vision and machine learning.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Online Course