Please answer part d True or False?a) Feature scaling speeds up gradient descent by making it require fewer iterations to get to a good solution.b) Feature scaling prevents the matrix x'x (used in the normal equation) from being non-invertable (singular/degenerate).c) Feature scaling is necessary to prevent the normal equation from getting stuck in local optima.d) Feature scaling speeds up gradient descent by making each iteration of gradient descent less expensive to compute.

There are some of the algorithms for example, the algorithms of Neural network gradient descent…

Answered: d) Feature scaling speeds up gradient…

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d) Feature scaling speeds up gradient descent by making each iteration of gradient descent less expensive to compute.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Please answer part d

True or False?
a) Feature scaling speeds up gradient descent by making it require fewer iterations to get to a good solution.
b) Feature scaling prevents the matrix x'x (used in the normal equation) from being non-invertable (singular/degenerate).
c) Feature scaling is necessary to prevent the normal equation from getting stuck in local optima.
d) Feature scaling speeds up gradient descent by making each iteration of gradient descent less expensive to compute.

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