Machine learning by doing is a series following the best machine learning tutorials and examples posted around the internet and ensuring they are 100% repeatable. Clearly defined version numbers for programming languages and packages, links to data sets and explanations of some of the lesser known functions we will encounter.
These examples are some of the best found on the web, but it is incredibly frustrating to find you are missing one small piece to re-create their results.
For the first post we follow along with Adam Geitgey in Part 3 of his “Machine Learning is Fun!” series.