The Machine Learning Field Guide - KDnuggets

We all start with either a dataset or a goal in mind. Once we've found, collected or scraped our data, we pull it up, and witness the overwhelming sight of merciless cells of numbers, more numbers, categories, and maybe some words! A naive thought crosses our mind, to use our machine learning prowess to deal with this tangled mess... but a quick search reveals the host of tasks we'll need to consider before training a model! Once we overcome the shock of our unruly data, we look for ways to battle our formidable nemesis. We start by trying to get our data into Python. It is relatively simple on paper, but the process can be slightly... involved. Nonetheless, a little effort was all that was needed (lucky us). Without wasting any time, we begin data cleaning to get rid of the bogus and expose the beautiful.