Starter Framework for Machine Learning Projects

Let’s summarize our story here. We started with Problem statement and Algorithm selection by formulating of the task of predicting which species of iris a particular flower belongs to by using physical measurements of the flower and then we prepare our project and load the associated dataset. We used a dataset of measurements that was annotated by an expert with the correct species to build our model, making this a supervised learning task (three-class classification problem). After that, we start exploring and visualizing the data to understand it, then split our data to training and test sets reaching to build our model and fit it by training and then test.