A Mini Backtest Orchestration Pattern for Financial ML

1. 1Build a backtest orchestration framework using Python
2. 2Configure a data pipeline to feed into the framework
3. 3Test the framework with a simple financial ML model
4. 4Apply the pattern to more complex models and scenarios
5. 5Compare results across different models and parameters

Data scientists and ML engineers on a team can benefit from this pattern to streamline their backtesting process and collaborate more effectively

💡 Connecting individual financial ML samples through a backtest orchestration pattern can improve workflow efficiency and collaboration

Streamline your financial ML backtesting with a mini orchestration pattern 💡