How you operationalize you ML models?

Kirill Kirikov
0 replies
I feel the pain that every-time when you've created an ML model in Jupyter notebook you need to wrap it into some flask application, then deploy it to AWS or GCP, add monitoring, logging, check for errors, and maintain high availability. Do you use any products that are solving this problem? Also, you can try using platform that we've just launched today and trying to solve the problem of productionalization of ML pipelines. And we need your feedback!
No comments yet