https://community.databricks.com/t5/machine-learning/ml-model/m-p/72597#M3346 <P>What's the best option to store your trained ML models</P> Tue, 11 Jun 2024 22:55:59 GMT UnniKAnat 2024-06-11T22:55:59Z https://community.databricks.com/t5/machine-learning/ml-model/m-p/72597#M3346 <P>What's the best option to store your trained ML models</P> Tue, 11 Jun 2024 22:55:59 GMT https://community.databricks.com/t5/machine-learning/ml-model/m-p/72597#M3346 UnniKAnat 2024-06-11T22:55:59Z https://community.databricks.com/t5/machine-learning/ml-model/m-p/72606#M3347 <P>Depending on how many you have, different solutions may be appropriate - and conveniently, you can use MLflow as a front end for most of these if you're working in Python. If you're working on personal projects, a local MLflow instance might be the right call. However, you can change the MLflow backend to be a database or remote, so you can store your trained models in the cloud (AWS, Google Cloud, etc.) or on remote resources not in the cloud (on-premises) including those with an HTTP endpoint.</P><P>For more information, here's the <A href="https://mlflow.org/docs/latest/tracking/backend-stores.html" target="_self">MLflow documentation</A> with additional resources on backend stores, including on Databricks integration.</P> Tue, 11 Jun 2024 23:03:54 GMT https://community.databricks.com/t5/machine-learning/ml-model/m-p/72606#M3347 mheffernan 2024-06-11T23:03:54Z