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We use data to advance science, make businesses more profitable, automate annoying tasks, and develop smart products. But there is a middleman between data and its usefulness: the model. The model represents a simplified aspect of the world; it’s the glue that connects data and world.

Statistics versus machine learning, frequentist versus Bayesian inference, causation or association, … There are many mindsets to consider for building models from data. Each of these modeling mindsets has its own assumptions, strengths, and limitations.

The best modelers, researchers, and data scientists don’t stubbornly stick to just one mindset. The best modelers mix and match the mindsets.

It can take years to truly grasp a new mindset. Most books and courses jump right into math and methods instead of discussing the fundamental mindset. But learning a new mindset doesn’t have to be this difficult. Modeling Mindsets introduces many cultures of learning models from data. Each mindsets enhances your modeling toolbox and makes you well-rounded and pragmatic modeler.

The book is packed with high-level explanations and illustrations. Quickly get an overview of the strengths and the limitations of each modeling mindset. Expand your mind when it comes to modeling the world using data.