Abstract: In this session we'll dive into recommendation systems powered with deep learning. We will understand the challenge and opportunity with online recommendations, and explore practical deep learning techniques for building recommendation systems. We will go over a hands on example of creating and training a recommendation model using PyTorch, and explore the model's performance and further optimizations.
Attendees will learn how to apply deep learning to the problem of recommendations and ranking, and how they can leverage PyTorch to rapidly implement recommendation systems for various business use cases.
Bio: Hagay has been busy building software for the past 15 years and still enjoys every bit of it (literally). He engineered and shipped products across various domains: from 3D medical imaging, through global scale web systems, and up to deep learning systems used at scale by engineers and scientists world-wide. He is currently based in the Silicon Valley, in sunny California, and focuses on democratizing AI and Machine Learning.