Recommendation systems are all around us. E-commerce companies like Amazon recommend products we are likely to buy based on our browsing behavior. Netflix suggests what shows we should watch based on our binging habits. Spotify builds a personalized playlist we would enjoy listening to, based on their understanding of what musical genre we are into.
In this talk, we will explore recent advances in the area of product recommendations in both research and practice. We will see how machine learning, design thinking, and solid data engineering principles are combined to create an engaging customer experience that positively impacts the bottom line.
We will look at how we use various deep learning architectures to obtain image and text embeddings that supplement user and product-based features to generate product recommendations that align closely with a consumer’s aesthetic preferences.
Director Data Science
Levi Strauss & Co.
02:40PM - Day 2
10:20AM - Day 2