Introduction to Deep Learning for Recommendation Systems
Introduction to Deep Learning for Recommendation Systems

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.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from Youtube
Vimeo
Consent to display content from Vimeo
Google Maps
Consent to display content from Google