Masterclass: Implications of Deep Learning Recommendation Systems - Jio Institute Skip to main content

Masterclass: Implications of Deep Learning Recommendation Systems

Masterclass by Murali Annavaram
Masterclass by Murali Annavaram
04 May 2023 17:00 - 18:30 (IST)
{ "name":"Masterclass: Implications of Deep Learning Recommendation Systems", "startDate":"01-14-2022", "endDate":"01-18-2022", "startTime":"10:15", "endTime":"23:30", "description":"Masterclass: Implications of Deep Learning Recommendation Systems", "options":[ "Apple", "Google", "iCal", "Microsoft365", "Outlook.com", "Yahoo" ], "trigger":"click", "custom_date":"05-04-2023 / 05-04-2023", "custom_time":"17:00 - 18:30", "timeZone":"Asia/Kolkata" }

Speakers

Watch the video

Event Gallery

Introduction

This masterclass will look at "The Magic of Recommendation Systems: Understanding Deep Learning and its Implications on Security and Privacy". Have you ever wondered how your favourite online services like Spotify, Netflix, and Amazon, provide you with such personalized and accurate recommendations? The answer lies in the deep learning machine learning models that capture vast amounts of information about our online behavior and use it to make recommendations. These models are trained on massive amounts of data, including sparse features like clicks, purchases, and mouse hovers on websites. In this webinar, our speaker will provide an overview of how current-generation recommendation systems work, and also delve into the implications of the data collected by these systems on user privacy and security. Join us as we explore the fascinating world of deep learning and its impact on our lives.

What Will You Learn?

  • Understand the workings of current-generation recommendation systems and how they make personalized recommendations for users.
  • Analyze the amount of data collected by recommendation systems and its impact on user privacy.
  • Recommendation systems, such as de-anonymization and tracking across interaction sessions.
  • Learn about the measures that can be taken to enhance the security and privacy of user data in recommendation systems.
  • Explore the scope of security and privacy research that needs to be conducted in this domain.