Mr. Ahmet Tugrul Bayrak
Ata Technology Platforms, Istanbul, Turkey
Speech Title: Exploring the Potential of Generative AI in Recommender Systems
Abstract: Generative AI technologies have a significant impact on various domains. One of these domains is recommender systems. Generative AI technologies are changing how recommender systems work by offering new ways to improve product recommendations and personalization. This talk explores how generative AI helps create and expand product bundles, improves customer engagement, and increases recommendation accuracy. Traditional methods, such as the Apriori algorithm and word embedding models like Word2Vec and FastText, are compared with generative AI to show their unique advantages and how they can work together. Real-world examples and experiments highlight how generative AI understands user preferences and generates better product bundles. These ideas show how recommendation systems can improve in practical ways across different industries.
Short Bio: Ahmet Tugrul Bayrak is the Data Science Manager at Ata Technology Platforms in Turkey. He holds a Bachelor of Science degree in Mathematical Engineering from Yildiz Technical University and another in Computer Engineering from The Technological University of the Shannon. Additionally, he attended Uppsala University for a Master's degree in Computer Science. Throughout his career, Mr. Bayrak has engaged extensively as a software engineer and data scientist. He has participated in numerous projects with a particular focus on Natural Language Processing and Recommender Systems. In addition to his contributions to industry practices, Mr. Bayrak is also actively engaged in academia, with his academic portfolio including many published papers.

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