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Curve Fitting with Python and SciPy: Moving Beyond Excel

·1 min
Python Scipy Machine-Learning Tutorial

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For engineers, curve fitting is a common task. Instead of relying on Excel, let’s use Python to find a function that fits the (x, y) data pairs. It’s a great opportunity to start using Python in your daily work!

Here is the repl link: https://replit.com/@oskrgab/curve-fit-python

Did you know that what you’re doing right now is actually machine learning? And to keep up with the hype, you’re using AI 😜. Nowadays, some terms are abused, and much of what we refer to as AI is simply analytics. In this case, it’s a simple linear regression.

The “curve_fit” function in scipy uses least squares to find the coefficients in an unconstrained problem. And there are some assumptions under which the linear regression model is valid:

  • Linearity/zero mean
  • Constant Variance
  • Independence (hard to check)
  • Normality

What can you do to check if these assumptions are valid? Can you create some plots? If so, what plots would you create?

(Hint: Calculate the residuals 😉)