The AI-Powered Super IC
Developing on Databricks: guide for AI engineers
Hosted by Maria Vechtomova and Başak Eskili
What you'll learn
Choose the right Databricks compute configuration
Understand what compute configurations you need to choose for your use case.
Understand Databricks Developer tools
Understand different options Databricks developers have: Databricks CLI, dbconnect, VS code extension, asset bundles.
Learn an optimal way to use the developer tools
Understand how to develop a Python project, package it, and execute it on a Databricks environment.
Why this topic matters
Any AI engineer must be able to write proper Python code. Unfortunately, this is not easy to achieve while working in a notebook, which is a predominant way of developing on Databricks.
In this session, we will show you alternative ways that will help you save time later when you move your project from a POC to production.
You'll learn from
Maria Vechtomova
MLOps Tech Lead, Databricks MVP
MLOps Tech Lead with 10+ YoE in machine learning and MLOps. Databricks MVP. Writing an O'Reilly book on MLOps with Databricks.
Başak Eskili
ML Engineer
ML Engineer with 6+ YoE. Currently working at booking.com in a feature store team, serving 200k RPS with P99.9 25ms latency.
Go deeper with a course
End-to-end MLOps with Databricks
Maria Vechtomova and Başak Eskili
MLOps Tech Lead | Databricks Beacon | 10+ years in Data & AI. Senior ML Engineer | 7+ years in Data & AI
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