New to QC - Many questions

I am grinding my way through boot camp and I have some questions before I get too deep into using this and paying for capability. While new to Python (lots of background in C++ & VB), I have been programming in TradeStation Easy Language for a while and have developed an enormous code base I want to get into a python platform. I really would like to get my custom strategies and algos into a platform like this for and be able to apply some AI/ML based optimization. So, here are my questions: Can you apply AI/ML methods/optimizations in this platform in a straightforward way? I have a lot of custom indicators/functions/strategies so can you build a code base on the QC platform? When I was looking at sample projects it seemed like you get a "main.py" and no way to add other files...

Hello Michael,

For getting started with implementing machine learning, QC currently allows the use of many Python libraries (link to the full list). If you are familiar with using any of these packages/frameworks, then implementing them is as simple as assigning inputs and outputs within your algorithm. You also might be interested in reading:

https://www.quantconnect.com/docs/research/machine-learning-research#Machine-Learning-Research-Introduction

For custom indicators, you can implement them manually (e.g., initialize a rolling window in self.Initialize, fill it when data arrives in self.OnData, and then when it is full, perform an action based on some result acquired using this window of data) or by using the Indicator class to create your own.

Lastly, you can add files in QuantConnect. The caveat being, however, that a main.py file must exist as the entrypoint to your algorithm and that all project files are of .py (or .cs if using C#) extensions. If files of other types are needed, read about the object store feature.

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