The first lecture from the Experimental Design and Common Pitfalls of Machine Learning in Finance series addresses the four horsemen that present a barrier to adopting the scientific approach to machine learning in finance.

The second lecture focuses on a protocol for backtesting and how to avoid the seven sins of backtesting. By implementing the research protocol outlined in these articles, an investment manager can avoid making the seven common mistakes when backtesting and building quant models.