This does an honest good job of walking through the beginnings, I would still say understanding/decomposing a decision tree and going through the details and choices /trade offs one makes with how they prepare the tree like binary split or discrete/binning for continuous data. What reducing entropy means, etc. Maybe even start with parametric versus nonparametric modeling pros/cons. You really get to see how probability and statistics is applied in the formulas that eventually will be thrown into a dot function in python.
There is a lot of content on pytorch, which is great and makes a ton of sense since it's used so heavily, where the industry needs a ton of help/support in is really the fundamentals. Nonetheless, great contribution!
There is a lot of content on pytorch, which is great and makes a ton of sense since it's used so heavily, where the industry needs a ton of help/support in is really the fundamentals. Nonetheless, great contribution!