Workshop: Building Real-Time ML Features with Feast, Spark, Redis, and Kafka

Posted Apr 12, 2022 | Views 802

# Data engineering

# Feature Stores

# Open Source

# Systems and Architecture

SPEAKER

Danny Chiao

Engineering Lead @ Tecton

Danny Chiao is an engineering lead at Tecton/Feast Inc working on building a next-generation feature store. Previously, Danny was a technical lead at Google working on end to end machine learning problems within Google Workspace, helping build privacy-aware ML platforms / data pipelines and working with research and product teams to deliver large-scale ML powered enterprise functionality. Danny holds a BachelorÕs degree in Computer Science from MIT.

+ Read More

SUMMARY

This workshop will focus on the core concepts underlying Feast, the open source feature store. WeÕll explain how Feast integrates with underlying data infrastructure including Spark, Redis, and Kafka, to provide an interface between models and data. WeÕll provide coding examples to showcase how Feast can be used to:

Curate features in online and offline storage
Process features in real-time
Ensure data consistency between training and serving environments
Serve feature data online for real-time inference
Quickly create training datasets
Share and re-use features across models

+ Read More

Watch More

1:00

Workshop: Operationalizing ML Features on Snowflake with Tecton

Posted Apr 12, 2022 | Views 730

# Data engineering

# Feature Stores

# Production Use Case

# Systems and Architecture

Redis? Dynamo? Cassandra? How to choose the right online store for your ML features.

Posted Jan 31, 2022 | Views 860

# Feature Stores

# Systems and Architecture

Weaver: CashAppÕs Real Time ML Ranking System

Posted Apr 12, 2022 | Views 765

# Feature Stores

# Production Use Case

# Systems and Architecture