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Quick Success Data Science
Easy Quadratic Optimization with Python
Maximizing website ad revenue
I studied mathematics between 1965 and 1981 (yes, I’m that old). Back then, most math teachers did a terrible job teaching math. In fact, around 1979, my college calculus teacher held up our new textbook and complained, “Math teachers don’t write textbooks for math students, they write them for other math teachers!” I didn’t fully appreciate this until around 2013, when I thumbed through my daughter’s 7th-grade math book and was blown away by how interesting and useful it was. I actually envied her studying math.
When I first learned the quadratic equation (ax² + bx + c = 0), I thought it was just a way to draw a parabola. That’s about all we did with it. But boy, was I wrong. This famous formula is a powerful optimization tool. Despite its simplicity, it can solve riddles like:
- What ticket price will maximize movie theater revenue?
- What rent should an apartment building charge to maximize monthly income?
- What is the optimal amount of fertilizer to maximize crop yield?
In this Quick Success Data Science project, we’ll use the quadratic equation to determine the optimum number of ads a webpage needs to maximize its ad revenue.
