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1
Intro
2
Challenges
3
Unified MLOps
4
Feature Store Demonstration
5
Databricks Demo
6
Training Sets
7
Feature Serving
Description:
Explore a revolutionary approach to MLOps in this 29-minute talk from Databricks. Learn how to scale machine learning models without increasing latency by combining a database, feature store, and machine learning. Discover Splice Machine, a hybrid database built on HBase and Spark, which offers a unique single-engine feature store and deploys ML models as database tables. Understand how HBase enables millisecond feature serving and prediction generation, while Spark facilitates complex training set creation and large-scale ML predictions. Gain insights from the speaker's experience at NASA's AI lab and various software companies. Watch a demonstration of Splice Machine's capabilities and its integration with Databricks through a simple JDBC connection. Delve into topics such as unified MLOps, feature store functionality, training set generation, and feature serving for efficient model deployment and scaling.

Unified MLOps: Feature Stores and Model Deployment

Databricks
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