The School of Computer Science at the University of Windsor is pleased to present...
Technical Workshop Presentation by: Shaghayegh Sadeghi - Ph.D. Candidate
Recommendation Systems in Python (Part 3)
Presenter: Shaghayegh Sadeghi – Ph.D. Candidate
Date: Thursday, November 10th, 2022
Time: 12:00 pm – 1:00 pm
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
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.
Knowledge of Supervised Learning with scikit-learn and pandas
- 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 rating
- Finding similarly liked movies
- Using K-nearest neighbours
- Stepping through K-nearest neighbours
- Getting KNN data in shape
- KNN predictions
- Item-based or user-based
- Comparing item-based and user-based models
- Which one to choose?
Shaghayegh is a Ph.D. candidate and research assistant in the School of Computer Science. Her main research interest is in using Graph Neural Networks for graph embedding.
Research interest: Privacy and security of machine learning, Biometrics, and Digital Forensics.