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4 changes: 3 additions & 1 deletion python_scripts/02_numerical_pipeline_scaling.py
Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,9 @@
#
# * Many models such as logistic regression use a numerical solver (based on
# gradient descent) to find their optimal parameters. This solver converges
# faster when the features are scaled.
# faster when the features are scaled. Since the numerical solver converges
# step by step (called **iterations**) to the optimal solution, the total
# number of such iterations is reduced.
# ```
#
# Whether or not a machine learning model requires scaling the features depends
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