Hi QuantConnect Community,

I am contemplating about a trading project with the following workflow:

1. The research part includes fitting a random forest model on historical data and save the model

2. The live trading/backtesting part would involve invoking the saved model and feed in real-time data to get a prediction response

I am wondering if I could do both 1 and 2 on the QuantConnect Python Platform? Any pointers would be much appreciated. Thanks a lot.