This course covers the most neglected yet critical skills in machine learning, four vital techniques that are very rarely covered – most courses and books omit them entirely.
1) UPLIFT MODELING (AKA PERSUASION MODELING): When you're modeling, are you even predicting the right thing?
2) THE ACCURACY FALLACY: When evaluating how well a model works, are you even reporting on the right thing?
3) P-HACKING: Are your simplest discoveries from data even real?
4) THE PARADOX OF ENSEMBLE MODELS: Do you understand how they work, even though they seem to defy Occam's Razor?Lee mas.
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The techniques and tools covered in Four Rare Machine Learning Skills All Data Scientists Need are most similar to the requirements found in Científico de datos data science job advertisements.
