Machine learning is about extracting knowledge from data. It is a research field at the intersection of statistics, artificial intelligence, and computer science and is also known as predictive analytics or statistical learning. The application of machine learning methods has become present in everyday life. From recommendations of which movies to watch, to which products to buy and recognising your friends on social media, machine learning algorithms that learn from input/output pairs are called supervised learning algorithms because a “teacher” provides supervision to the algorithms in the form of the desired outputs for each example that they learn from. As creating a dataset of inputs and outputs is often a manual process, supervised learning algorithms are well understood and their performance is easy to measure. As stated before, we will be covering the Iris Species classification problem — a typical test case for many statistical classification techniques in machine learning.