The ML Engineer's Workshop: Smoothly Connecting R and Power BI
summary
An ML engineer demonstrates a practical toolkit for building end-to-end analytics solutions using R (and sometimes Python), SQL, and Power BI. The talk explains how to integrate these technologies to create production-ready, deployable ML-enabled reports and applications (cloud or on-premises) for analysts.
AI-written summary · about
chapters (10)
- 0:00Introduction
- 3:15R and Power BI basics
- 7:29R limits and visuals
- 13:30Data from R/Python
- 16:23Machine learning models
- 22:03Handling missing data
- 26:01Time series forecasting
- 30:59Power BI ML features
- 35:15Anomaly detection
- 39:54Summary and Q&A
related talks
18mEmpowering Business Through Data
25m"Data Engineering: The World Between Worlds"
55mML with real impact driven by OS technologies
38mUnleashing the Power of Analytics Engineering
33mPanel Discussion
50mDataOps 101 – A Better Way to Develop and Deliver Data Analytics
48mGit off my lawn: Mastering Power BI Deployments with Git Integration
27mA Look Inside Applied Machine Learning