This community-built FAQ covers the “Learning Rate” exercise from the lesson “Linear Regression”.
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This exercise can be found in the following Codecademy content:
Data Science
Machine Learning
FAQs on the exercise Learning Rate
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There’s a bug in Chapter 9 - Linear Regression. It says " We have imported two new lists representing how the b value changed with different learning rates:"…
bs_000000001 and bs_01 – but neither is imported or can be imported into the exercise.
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We derived the gradients of intercept and loss using calculus. So the resulting formulas will return 0 for the minimum and therefore the best b (intercept) or m (slope).
So wouldn’t be the optimal way for finding the best b / m to just solve the equations? Equation for m:
0 = 2/N * SUM(-x_i * (y_i * - (m * x_i + b)), i=1, N)
Now resolve m. I didn’t try it, but I think it should be possible to solve the equation and then you have a general formula for finding b / m.
