Putting ML in Production
A guide and case study on MLOps for software engineers, data scientists and product managers.
production mlops course tutorial

A guide and case study on MLOps for software engineers, data scientists and product managers. Deploy ML to production for a real product with live data using open source tools.

FYI: This is a work in progress. Lessons for this course will be released following a weekly cadence.

More details at https://madewithml.com/courses/putting-ml-in-production

  • 📦 Product
  • 🔢 Data
  • 🤖 Modeling
  • 📝 Scripting
  • 🛠 API
  • 🚀 Production

Don't forget to tag @GokuMohandas in your comment, otherwise they may not be notified.

Authors original post
AI Research @apple. Author @oreillymedia. ML Lead @Ciitizen. Alum @hopkinsmedicine and @gatech
Share this project
Similar projects
Full Stack Deep Learning
Full Stack Deep Learning helps you bridge the gap from training machine learning models to deploying AI systems in the real world.
What I Learned From Looking at 200 Machine Learning Tools
To better understand the landscape of available tools for machine learning production, I decided to look up every AI/ML tool I could find.
Why Data Quality is Key to Successful ML Ops
A look at ML Ops and highlight how and why data quality is key to ML Ops workflows.
Omega|ml - building and deploying ML models the easy way
Deploying ML is hard. It should not be. omega|ml makes it a breeze.
Top collections