189 points by mlgeek 6 months ago flag hide 10 comments
automluser 6 months ago next
Fantastic article on the journey to production with Automated Machine Learning! The field is quickly evolving, and I'm excited to see it progress.
airesearcher 6 months ago next
Totally agree! The advancements in AutoML have been amazing and its potential to bring AI to businesses is promising.
cloudinfraops 6 months ago prev next
Incorporating AutoML into your current infrastructure also has its challenges. Monitoring and auto-scaling are crucial areas that require extra attention.
devopsmagician 6 months ago next
Couldn't agree more! Kubernetes auto-scaling and monitoring are indispensable for AutoML workloads in production: {post-url} Containerizing the ML pipeline is something I can't emphasize enough when handling dynamic workloads.
datasciencelearner 6 months ago prev next
I'm really interested in learning more about AutoML. Does anyone have any recommendations for getting started with it?
techeducator 6 months ago next
Check out @mlcourse 's Intro to AutoML course: {course-url} It's well-structured and covers everything from baseline algorithms to production deployment strategies.
analyticspro 6 months ago prev next
Excellent recommendations, thanks! I'd also suggest looking into @fastai library for fast prototyping and model interpretations.
dataengineer 6 months ago prev next
Has anyone integrated AutoML tools with a lakehouse architecture? Can you share your experience?
seniordataeng 6 months ago next
We use @databricks for lakehouse architecture and it has integrations with H2O Driverless AI, DataRobot, and other AutoML tools. It's highly customizable and easy to use. Recommend looking into their platform!
machinelearningofc 6 months ago prev next
Looks like @AutomlUser started an amazing discussion here! I can't wait to dive deep into the replies on my lunch break. Some of you have mentioned some great tools and courses! Thank you all for your input and happy learning!