Are you building a machine learning recommender system or planning to? 

Then you won’t want to miss apply(recsys), a free, virtual event that focuses on the specific challenges of building recommender systems. 

Sign up today to learn from industry experts from Slack, ByteDance, Feast, and more. Topics include: 

• Best-practice development patterns

• Systems architecture

• Tooling and infrastructure of choice

• Building and managing real-time data pipelines

• Serving predictions at scale

REGISTER FOR FREE

⭐Highlight: Slack’s Unified End-to-End ML Infrastructure to Generate Recommendations⭐

Katrina Ni, a machine learning engineer at Slack, will dive into Slack’s Recommend API, a unified framework the team built that enables them to quickly bootstrap new recommendation use cases. 

These recommenders reuse a common set of infrastructure for every part of the recommendation engine, such as data processing, model training, candidate generation, and monitoring.

Register today to learn more!

apply() is an event series for machine learning and data teams to discuss the practical data engineering challenges faced when building real-time machine learning systems. Participants learn from industry experts and share best practices with the community.