Unveiling the Magic: How Scikit-learn’s fit() finds Your "Best Fit Line" (And where the Cost Function Hides)
A machine learning (ML) Python scripting tutorial.
If you’ve dipped your toes into machine learning with Python, chances are you’ve written lines of code that look something like this:
Python
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)
And just like that, you’ve got yourself a “best fit line” for your data! It feels almost magical, doesn’t it?
