DOC: Improve Ridge regression example — fix typo, clarify title, add legend (scikit-learn#31539)

Co-authored-by: Dhyey Findoriya <dhyeyinf323@gmail.com>

Author: dhyeyinf

examples/linear_model/plot_ridge_path.py

@@ -22,7 +22,7 @@
 squared loss function and the coefficients tend to zero.
 At the end of the path, as alpha tends toward zero
 and the solution tends towards the ordinary least squares, coefficients
-exhibit big oscillations. In practise it is necessary to tune alpha
+exhibit big oscillations. In practice it is necessary to tune alpha
 in such a way that a balance is maintained between both.
 
 """
@@ -63,6 +63,9 @@
 ax.set_xlim(ax.get_xlim()[::-1])  # reverse axis
 plt.xlabel("alpha")
 plt.ylabel("weights")
-plt.title("Ridge coefficients as a function of the regularization")
+plt.title("Ridge Coefficients vs Regularization Strength (alpha)")
 plt.axis("tight")
+plt.legend(
+    [f"Feature {i + 1}" for i in range(X.shape[1])], loc="best", fontsize="small"
+)
 plt.show()