AI/ML for Scalable Recommender Systems

Machine Learning Meetups are back after summer break! In September we will learn more about AI/ML for Scalable Recommender Systems by Jakub Mačina.

Talk will be in English (Slovak optional if audience is Slovak only) followed by discussion and networking with refreshments. Our talk will be recorded and will appear on our youtube channel afterwards.

Please help us manage the capacity by registering via EVENTBRITE here: https://bit.ly/2whfjKJ

Synopsis of the talk:

Recommender systems are successfully used in several domains such as e-commerce or multimedia recommendation. In the e-commerce field, increasing number of companies utilize recommender systems to offer a personalized shopping experience for their customers.

In this talk, we will provide an overview of typical recommender system architecture, approaches used in the real-world applications and we highlight the challenges encountered by industry practitioners. We will discuss basic approaches, such as matrix factorization and text mining, and move on to deep learning techniques for recommendation. In the real-world case study we will show how to capture attributes of products into a dense (latent) embedding representation. Finally we will focus on evaluation metrics and interactive learning for optimizing long-term revenue of retailers. Everybody with an interest in machine learning is welcomed.

About speaker:

Jakub Macina is the Recommendations Team Lead at Exponea. He graduated from the Slovak University of Technology with specialization in machine learning and information retrieval. His research background is in the field of recommender systems with a publication at the premier conference on recommender systems research ACM RecSys. He is passionate about movement and open source software.

Exponea Experience Cloud is an award-winning customer experience and data management platform that boosts e-commerce growth with AI-powered engagement automation and helps improve company culture with improved cross-department collaboration and customer centricity.

See you in September!

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