StatQuest has a clear explanation of ROC and AUC – a critical piece of evaluating machine learning models.
Gradient Descent is the workhorse behind much of Machine Learning. When you fit a machine learning method to a training dataset, you’re almost certainly using Gradient Descent.
The process can optimize parameters in a wide variety of settings. Since it’s so fundamental to Machine Learning, Josh Starmer of StatQuest decided to make a “step-by-step” video that shows exactly how it works.
Heads up: there is some singing.