I am pretty excited about the capabilities of LoudML with respect to Predictive analytics and anomaly detection. However I am beginner to LoudML.
My specific query is about the capabilities of LoudML to run Statsmodels SARIMAX & RNN based algorithms from Python ML Libraries. Can this be programmed from LoudML as of current release?
Any demonstrative link would be helpful as well.
Thanks !
Hello @rswarnkar,
Hello and Welcome! I’m not sure. LoudML is a forked from Influx. However you might look into just using the python client? Here’s an example for how to integrate Keras with InfluxDB for LTSM bases stock predictions. Here’s an example for integrating prophet and influx. Maybe something in there is useful to you?
Hello Ana,
Thanks a lot for the reference. I would go through these and come back for queries.
A little background: my workplace involves a lots of system monitoring data and the user complaint tickets. There is need to have these correlated and predicted. I have some experience with SARIMA and RNN and would like to design a production setup that would do this on continuous basis instead of writing and running ipynbs. I came across the influx db for dealing with timeseries but also looking for sometool that does this readily with some ML tuning and python programming (nice integration).
I would have look and get back.
Thanks again 
