Building a Predictive Model
Building a predictive model should be tightly linked with data science theory. Clearly defining the problem, ensuring that it’s ethical, and accurately representing your results are critically important to a model’s success.
Once you have a good idea of the problem and have thought it through from multiple perspectives there are a series of steps that you can follow to learn more about the data and choose the model type. The beauty of data science is that there are many solutions to each problem. This section is designed to provide a high-level overview of many of the core components. You’re encouraged to learn more and add new processes as you build your skills as a data practitioner.