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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
63,068 ratings

About the Course

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

AA

Invalid date

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

AM

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I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

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4601 - 4625 of 7,244 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By M S

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Sep 22, 2018

IT was a great course

By hiyouga

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Sep 11, 2018

A very useful course!

By anis

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Sep 9, 2018

the best course ever!

By David B

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Sep 9, 2018

Continued brilliance.

By Tran T D

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Aug 8, 2018

another great course!

By Laurenz R

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Jun 3, 2018

Very good explanation

By KIBO

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Mar 25, 2018

very good ! Thank you

By Saurabh P

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Feb 17, 2018

Very valuable course.

By Aleksei T

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Jan 6, 2018

That was cool as well

By Ziemek T

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Dec 30, 2017

great course, thanks!

By Chenhao W

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Dec 4, 2017

Thank you Andrew Ng !

By Cheng H

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Nov 19, 2017

Grading is a bit slow

By Bruce J

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Oct 7, 2017

Absolutely wonderful!

By Deleted A

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Sep 29, 2017

NIce course I like it

By Walter L

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Sep 21, 2017

Really useful course!

By Jiarui F

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Sep 20, 2017

it is really helpful!

By Zack A

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Sep 12, 2017

nice tensorflow intro

By Bernard R

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Sep 9, 2017

Very valuable course!

By Enoch C Y S

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Sep 8, 2017

Very GOOD!!!!!!!!!!!!

By YongyiWang

•

Sep 6, 2017

This course is great!

By Sunshine

•

Sep 2, 2017

thanks for the course

By Chen Y

•

Aug 13, 2017

Class_label = "Great"

By Sukhjot K

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Jul 6, 2023

Very well explained.

By Sifal K

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Dec 5, 2022

thank you very much!

By Giang L T

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Aug 19, 2021

this course is great