Machine Learning project strategy for optimizing an objective including Orthogonalization, Single Number Evaluation Metrics, Optimizing and Satisficing Metrics, Training, Dev (Validation) and Test Sets, changing the Metric Function for unexpected scenarios, Accuracy Level Benchmarks including Bayes Optimal Error, Human-level Performance, Variance and Avoidable Bias, and optimization decisions based on errors
