This repository contains notebooks used over at calmcode.io.
An overview of how to use scikit-learn.
Course is found here and the notebook can be found here.
How can you customise metrics to pick the right model.
Course is found here and the notebook can be found here.
How to apply post-processing in scikit-learn.
Course is found here and the notebook can be found here.
Can preprocessing suddenly make an algorithm work?
Course is found here and the notebook can be found here.
Can we model by using Natural Intelligence?
Course is found here and the notebook can be found here.
Is smoking good for you? Or can we lie with statistics?
Course is found here and the notebook can be found here.
When is lack of sleep causing damage? When is it significant?
Course is found here and the notebook can be found here.
Is the conclusion different if we don't assume all days are equal?
Course is found here and the notebook can be found here.
How can we balance risk and reward?
Course is found here and the notebook can be found here.
Can you compile towards a GPU by writing code like numpy?
Course is found here and the notebook can be found here.
How do you practically solve the nearest neighbor problem.
Course is found here and the notebook can be found here.
How comprehensions work in python.
Course is found here and the notebook can be found here.
How to fit models with partial_fit.