Scikit-learn is an amazing Python library with unrivaled documentation, designed to provide a consistent API to dozens of algorithms. It is built upon, and is itself, a core component of the Python scientific stack, which includes NumPy, SciPy, pandas, and matplotlib. Here are some of the areas scikit-learn covers: classification, regression, clustering, dimensionality reduction, model selection, and preprocessing.
We'll look at a few examples. First, we will build a classifier using our iris data, and then we'll look at how we can evaluate our model using the tools of scikit-learn:
- The first step to building a machine learning model in scikit-learn is understanding how the data must be structured.
- The independent variables ...
