Build and judge a training set rather than accepting one, well enough to say what a model will be good at before it is trained, and to spot the three data faults that explain most disappointing results
Where Training Data Comes From
A model is mostly its data, and almost nobody looks at the data. This course covers collecting it, cleaning it, removing the duplicates that quietly ruin it, and the contamination that makes a benchmark lie to you.
8 lessons, written and corrected before you arrived. Reading them here needs no account. The first reads the whole way through; the others open and then stop, because a page nobody owns cannot tell who is reading it. Starting the course gives you your own copy, where every idea has problems standing under it and you can ask about any sentence.