Gradient descent is one of those machine learning concepts that looked intimidating to me. But as is the case with learning anything new, starting with the simplest version of a concept can provide the building blocks required for more complex understanding.
Today I took such a step (pun intended for those that already know gradient descent) by reading through an example that uses gradient descent to estimate the intercept and slope of a straight line. It’s a lengthy example and I had just a few minutes to review it but with more time tomorrow, I will continue to take iterative steps towards understanding gradient descent.
