Data Science Life Cycle 101 for Dummies like Me

Predictive modeling is where machine learning finally comes into your data science project. I use the term predictive modeling because I think a good project is not one that just trains a model and obsesses over the accuracy, but also uses comprehensive statistical methods and tests to ensure that the outcomes from the model actually make sense and are significant. Based on the questions you asked in the business understanding stage, this is where you decide which model to pick for your problem. This is never an easy decision, and there is no single right answer. The model (or models, and you should always be testing several) that you end up training will be dependent on the size, type and quality of your data, how much time and computational resources you are willing to invest, and the type of output you intend to derive. There are a couple of different cheat sheets available online which have a flowchart that helps you decide the right algorithm based on the type of classification or regression problem you are trying to solve.