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DIY Machine Learning for Industrial Operations in Energy and Manufacturing

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Engineers and operators in energy or manufacturing want to harness AI without writing code?
Join our live webinar and learn how to build and run machine learning models on live industrial data—no data science team required.

Today, building a predictive alert system for critical industrial processes often requires handing off the task to IT and data science teams, introducing delays and complexity. For example, a chemical process engineer might know exactly what signals indicate a risk of reactor overheating, but lack the coding skills to implement a predictive alert system. If you know your process, why wait? We're giving you the tools to act—fast.

The Solution: EOT’s Twin Sight ML Workbench & CrateDB
  • Real-time data to insight pipeline
  • Plug in your models, visualize results
  • Works with SCADA, PI Systems, Snowflake, and more
Ready to empower your operations with DIY Machine Learning?

What you will learn
  • Deploy ML Without Code using EOT’s Twin Sight ML Workbench—connect real-time data, run models, and visualize predictions instantly
  • Fast, Scalable Data Handling with CrateDB’s high-ingest, sub-second querying, and flexible storage for any data type
  • Cost-Effective, Anywhere Deployment: From cloud to edge, avoid hidden costs and scale on your terms
  • AI + SQL Simplicity: Use familiar tools (like SQL) and even ChatGPT to help generate Python scripts
Details

July 1, 2025

Webinar

CrateDB
Venue

Online

Organizer

CrateDB