Transfer Learning

Datacast Episode 63: Real-World Transfer Learning with Azin Asgarian

Datacast Episode 63: Real-World Transfer Learning with Azin Asgarian

Azin Asgarian is currently an applied research scientist on Georgian’s R&D team, where she works with companies to help adopt applied research techniques to overcome business challenges. Azin holds a Master of Science in Computer Science from the University of Toronto and a Bachelor of Computer Science from the University of Tehran. Before joining Georgian, Azin was a research assistant at the University of Toronto and part of the Computer Vision Group, where she worked on the intersection of Machine Learning, Transfer Learning, and Computer Vision. In addition, due to her interest in HealthCare, she has worked on various healthcare projects as a research assistant at University Health Network.

Recommendation System Series Part 3: The 6 Research Directions of Deep Recommendation Systems That Will Change The Game

Recommendation System Series Part 3: The 6 Research Directions of Deep Recommendation Systems That Will Change The Game

In this post and those to follow, I will be walking through the creation and training of recommendation systems, as I am currently working on this topic for Master Thesis. Part 3 addresses the limitations of using deep learning-based recommendation models by proposing a couple of research directions that might be relevant for the recommendation system scholar community.