Talk: Deep Learning for Recommender Systems by Jakub Mačina, Machine Learning Engineer, Exponea
Recommender systems are driving business value through personalisation for customers of Amazon, Netflix or Spotify. This talk will provide an overview of traditional and deep learning recommender system approaches and highlight the challenges encountered by industry practitioners such as extreme data sparsity. Real-world case study will show how to capture users varying tastes and products into a dense (latent) embeddings representation in order to design a scalable recommender system architecture.
Find out more about the event here:
The Talk "Deep Learning for Recommender Systems" by Jakub Mačina @dmacjam at the 29th #Vienna #DeepLearning #Meetup is available on Youtube: https://t.co/fqhDaoOmcW #VDLM #ai #artificialintelligence #recommendersystems— Tom Lidy (@LidyTom) October 1, 2019