Machine Learning: Recommender Systems & Dimensionality Reduction

Full Details
Level
Price
Common Core
Images
No items found.

About this Course
Case Study: Recommending Products How does Amazon recommend products you might be interested in purchasing? How does Netflix decide which movies or TV shows you might want to watch? What if you are a new user, should Netflix just recommend the most popular movies? Who might you form a new link with on Facebook or LinkedIn? These questions are endemic to most service-based industries, and underlie the notion of collaborative filtering and the recommender systems deployed to solve these problems. In this fourth case study, you will explore these ideas in the context of recommending products based on customer reviews. In this course, you will explore dimensionality reduction techniques for modeling high-dimensional data. In the case of recommender systems, your data is represented as user-product relationships, with potentially millions of users and hundred of thousands of products. You will implement matrix factorization and latent factor models for the task of predicting new user-product relationships. You will also use side information about products and users to improve predictions. Learning Outcomes: By the end of this course, you will be able to: -Create a collaborative filtering system. -Reduce dimensionality of data using SVD, PCA, and random projections. -Perform matrix factorization using coordinate descent. -Deploy latent factor models as a recommender system. -Handle the cold start problem using side information. -Examine a product recommendation application. -Implement these techniques in Python.
Subtitles available in English

Full Details
Formats: 
Part of resource: 
Posted 
Mar 2023
This resource has religious influence.

Similar resources

About University of Washington

The UW is one of the world’s preeminent public universities. Our impact on individuals, our region and the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship. Ranked No. 7 in the world on the U.S. News & World Report’s Best Global Universities rankings, the UW educates more than 54,000 students annually. We turn ideas into impact and transform lives and our world. For more about our impact, visit our news site, UW News.

So what defines our students, faculty and community members? Above all, it’s our belief in possibility and our unshakable optimism. It’s a connection to others near and far. It’s a hunger that pushes us to tackle challenges and pursue progress. It’s the conviction that together we can create a world of good. Join us on the journey.

More by University of Washington

thumbnail
Refraction
Refraction
2nd - 6th
thumbnail
Practical Predictive Analytics: Models and Methods
Practical Predictive Analytics: Models and Methods
College
thumbnail
Business English: Planning & Negotiating
Business English: Planning & Negotiating
High School - College
thumbnail
Machine Learning Foundations: A Case Study Approach
Machine Learning Foundations: A Case Study Approach
College
thumbnail
Machine Learning: Classification
Machine Learning: Classification
High School - College
thumbnail
Machine Learning Capstone: An Intelligent Application with Deep Learning
Machine Learning Capstone: An Intelligent Application with Deep Learning
College