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Recommendation System with Deep Learning and PyTorch
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Speaker:
Hagay Lupesko - Engineering Leader, AI and ML, Facebook
Abstract:
In this session we'll dive into recommendation systems: understand the problem of recommendations, machine learning techniques for building such systems, and will focus on modern neural network architectures for recommendations. We will go over a hands on example of creating and training a recommendation model using PyTorch, and explore model design and deployment tradeoffs.
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.
Hagay Lupesko - Engineering Leader, AI and ML, Facebook
Abstract:
In this session we'll dive into recommendation systems: understand the problem of recommendations, machine learning techniques for building such systems, and will focus on modern neural network architectures for recommendations. We will go over a hands on example of creating and training a recommendation model using PyTorch, and explore model design and deployment tradeoffs.
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.
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