Building a machine learning model isn’t always as easy as running .fit() and calling it a day. Sometimes, you need to eke out a little more accuracy, because even a 1% improvement can mean a lot to the bottom line. Many machine learning models have a lot of buttons and knobs you can adjust. Changing one value here, tweaking another value there, checking the accuracy one at a time, making sure it’s generalizable and not overfitting… it’s a lot of work to find the right model. Needless ...
