Matrix Factorization and Advanced Techniques
About this Course
In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. Then you will learn about techniques that combine the strengths of different algorithms into powerful hybrid recommenders.Created by: University of Minnesota

Related Online Courses
This Specialization is intended for anyone looking to take control of their finances. Through these five courses, you will cover a variety of personal finance topics, including budgets, investing,... more
This course is for anyone that wants to learn more about bias and how it can affect business, relationships, and communities. The course begins with an exploration of the word bias and its many... more
This course portrays how Copilot can be leveraged for cybersecurity. It provides a general overview as well as detailed use case demonstrations for Cybersecurity practitioners who want to augment... more
This course will evaluate best practices in transportation networks, thoroughfares, and streetscape designs for the effective movement of people, goods, and services in a region. Sustainable public... more
The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as... more