The School of Computer Science is pleased to present...
Technical Workshop
Presenter: Shaghayegh Sadeghi
Date: Wednesday, January 31st, 2024
Time: 3:00pm – 4:00pm
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
Abstract: In this workshop, students will learn everything they need to know to create their own recommendation engine. Through hands-on exercises, students will get to grips with the two most common systems, collaborative filtering, and content-based filtering. Next, students will learn how to measure similarities like the Jaccard distance and cosine similarity, and how to evaluate the quality of recommendations on test data using the root mean square error (RMSE).
By the end of this course, students will have built their very own movie recommendation engine and be able to apply their Python skills to create these systems for any industry.
Workshop Outline:
Collaborative filtering
Pivoting your data
Finding similar users
Challenges with missing values
Compensating for incomplete data Finding similarities
User-based to item-based
Similar and different movie ratings
Finding similarly liked movies
Using K-nearest neighbors
Stepping through K-nearest neighbors
Getting KNN data in shape
KNN predictions
Item-based or user-based
Comparing item-based and user-based models
Which one to choose?
Matrix Factorization and Validating Your Predictions
Dealing with sparsity
Matrix sparsity
Limited data in your rows
Matrix multiplication
Matrix factorization
Identifying latent features
Information loss in factorization
Singular value decomposition (SVD)
Normalize your data
Decomposing your matrix
Recalculating the matrix
Making recommendations with SVD
Validating your predictions
Calculating RMSE
Comparing recommendation methods
Prerequisites: Knowledge of Supervised Learning with scikit-learn and pandas Biography: Shaghayegh is a Ph.D. student at the School of Computer Science (University of Windsor). Her main research interest is in biological network embedding.
Biography:
Shaghayegh is a Ph.D. student at the School of Computer Science (University of Windsor). Her main research interest is in biological network embedding.