Dear all,

Newbie here with the QC platform.

I looked around the forum and also reddit and find that some people advocate running research locally offline if there is a lot of parameter tuning or training ML models.

My projects are mostly based on hard code rules now and I am attempting to move towards using ML/DL based research which I hope is less manual and efficient in detecting signals.

I have a beginner question on how does “research offline” works? 

  • Data: I searched around the forum and see that data are only free on cloud. If I want to do it offline, how much more do I need to pay? Or is it not even an option.
  • How does it improve the speed running locally vs in the web IDE? I know this maybe a stupid question. My research flow is now code it in the main.py file in Web IDE, spent loads of time backtesting it, investigate the backtest result alongside TradingView, update main.py and loop again….. It is pretty slow and inefficeint and I would really like to know how (1) running in research.ipynb in Web IDE save time in research (understand research.ipynb does not support coarse selection which is essential to my strategies) and (2) running locally helps save time
  • Parameter searching. Is there a way to do it without paying extra fees?


Many thanks for any guidance in advance!