Key takeaways and lessons learned

Important insights to keep in mind as you proceed to the practice of ML for trading include:

  • Data is the single most important ingredient
  • Domain expertise helps realize the potential value in the data, especially in finance
  • ML offers tools for many use cases that should be further developed and combined to create solutions for new problems using data
  • The choice of model objectives and performance diagnostics are key to productive iterations towards an optimal system
  • Backtest overfitting is a huge challenge that requires significant attention
  • Transparency around black-box models can help build confidence and facilitate adoption

We will elaborate a bit more on each of these ideas.

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