Always start with a stupid model, no exceptions. – Insight Data

For more content like this, follow Insight and Emmanuel on Twitter. When trying to develop a scientific understanding of the world, most fields start with broad strokes before exploring important details. In Physics for example, we start with simple models (Newtonian physics) and progressively dive into more complex ones (Relativity) as we learn which of our initial assumptions were wrong. This allows us to solve problems efficiently, by reasoning at the simplest useful level. The exact same approach of starting with a very simple model can be applied to machine learning engineering, and it usually proves very valuable.