Sometimes you want to use estimators from one package but methods from another. Maybe, like me, you want to use scikit-learn's grid searching cross validation function with an estimator from statsmodels. These two don't work together straight out of the box, but by writing a quick wrapper, you can make a statsmodels estimator play nice with scikit-learn. »
For a machine learning course, I had to write code to implement the ID3 algorithm to train decision trees from scratch. Writing recursive functions can be challenging and even frustrating, particularly when you are a math/stats master's student just beginning his foray into the world of devops and computer science. Each piece of the unoptimized recursion I wrote is written out in gory detail here for your reading pleasure. »
The gradient descent algorithm turns up nearly everywhere in machine learning. This algorithm is intensely popular because it is excellent at solving certain types of optimization problems. It must be used thoughtfully, however, since it is not guaranteed to converge to global extrema. It's absolutely essential for machine learning engineers to understand the mathematics of this ubiquitous algorithm. »