Name: Deep Dive into Building Recommender Systems
Start: 2025-11-19T09:00:00-05:00
End: 2025-11-19T10:00:00-05:00

Recommender systems shape how people discover products, content, and experiences every day. But behind every great recommendation is a set of simple ideas that guide how these systems learn, adapt, and improve. In this session, Georgina Armstrong will break down the core concepts that make recommender systems work.

The session offers a clear and practical look at the principles behind effective recommendation engines, helping you understand how they support better engagement, smarter decisions, and more relevant experiences across industries.

madison

HUMAN + AI Interaction Science Lab ny

Technology

Artificial Intelligence

Machine Learning

Predictive Analytics

Business

Data Science

Human-Computer Interaction

Analytics: Outcomes, Experimentation Intelligence

Telecommunications Pros

Banking

Insurance

Data Analytics

Big Data

Jaime Oscar Barrial Castillo

AbdulKarriem Khan

Jessica Nicole

Sharon Zambonino

Dan S

John Hoy

Ray Lance

Deep Dive into Building Recommender Systems

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HUMAN + AI Interaction Science Lab ny

Deep Dive into Building Recommender Systems

HUMAN + AI Interaction Science Lab ny

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