Framing the machine learning problem

Machine learning problem framing, as defined in this section, is a technique and methodology to help specify and contextualize a machine learning problem in such a way that an engineering solution can be implemented. Without a solid approach to tackling machine learning problems, it can become very hard to extract the real value of the undertaking.

We will draw inspiration from the approaches of companies such as Amazon and Google, which have been successfully applying the technique of machine learning problem framing.

The machine learning development process is highly based on the scientific method. We undergo different stages of stating a goal, data collection, hypothesis testing, and conclusion. It's expected that we will cycle through the different stages of the workflow until either a good model is identified or it becomes apparent that it's impossible to develop one.

The following subsections depict the framework that...