i have a few questions regarding H2O AI. As per my understanding, h2o AI powers Auto ML functionality. but need to integrate my own python jupyetr ML model. so my questions are,
- Can we use H2O AI without Auto ML and with our own python jupyter ML algorithm?
- If yes, can we integrate that own manual scripted ML with Snowflake?
- If we can integrate our own scripted ml algorithm with snowflake, what are the advantages of doing it that way? instead of an own manually-created python ML algorithm?
H2O.ai offers a bunch of ML solutions: h2o-3, driverless ai, hydrogen torch to name the main ones.
Driverless AI is AutoML driven, the user has, however, an option to provide a custom recipe (in Python) to customize it. Driverless AI has Snowflake integration.
H2O-3 is a framework that implements a collection of popular ML algorithms. H2O-3 also integrates an AutoML solution utilizing the built-in algos. There is no option to integrate a 3rd party solution into H2O-3 AutoML and to extend H2O-3 algos other than by coding in Java (small Python customizations can be made by providing eg. custom loss function in GBM).