Chevron Left
Back to Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
stars
63,504 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

AM

Oct 8, 2019

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

AA

Oct 22, 2017

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

Filter by:

2276 - 2300 of 7,286 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Kunal S S

•

Sep 18, 2017

Amazing course but could use better video explanations and should provide more resources

By Suresh A

•

Sep 3, 2017

The way Dr Ng puts the match together makes deep learning look very easy. Great teacher.

By Vincent L

•

Aug 31, 2017

Hands on and clear, this class will help to understand the more practical aspects of NN.

By Christopher A

•

Oct 7, 2023

Very insightful. I got to understand how the libraries I call in my code actually work.

By Abhinav T

•

Jan 3, 2021

Thanks for this wonderful journey dear Andrew Ng. Sir !

You are just wonderfully awesome

By Angana M

•

Dec 17, 2020

Very extensive course. The programming exercises help a lot in learning and practicing.

By Yuuki S

•

Nov 21, 2020

This course is very great and I can understand comprehensive technics of improving DNN.

By Bai D

•

Nov 9, 2020

Beautifully explained. Although little less hand holding in assignments wouldn't hurt..

By Fernando G M G

•

Oct 9, 2020

Great course. I love the final assigment. Ready for the next one in the specialization.

By Manas C B

•

Aug 31, 2020

The usage of each optimizer is clear enough so that I can apply it without any library.

By Antonio C L F J

•

Aug 13, 2020

Excellent course. Very well prepared to guide the apprentice in concepts and practices.

By João L

•

Aug 4, 2020

Great explanation about Hyperparameter tunning and tensorflow presentation was stunning

By Daniel A

•

Jul 13, 2020

On point approach to turn NN into customizable models for several use cases. Thank you!

By rtester 0

•

Jun 22, 2020

wonderful contents, to the point descriptions, short but deep and thorough explanation.

By Hetal K

•

Jun 14, 2020

Very important subject for deep neural network, thanks Andrew for excellent explanation

By Ravindra K

•

May 25, 2020

The course tells us about how can we improve accuracy by taking care of hyperparameters

By Gaurav S

•

Apr 12, 2020

very well conducted course. andrews helped me to understand the concepts pretty nicely

By Sandipan D

•

Apr 12, 2020

Love intro to tf. But I still hope there was the keras way of doing these - as in tf2.0

By Deepankar A

•

Mar 6, 2020

Really a very interesting course. Got me even more curious and involved into the topic.

By Anurag S

•

Dec 26, 2019

Amazing course taught by amazing instructors. I feel hugely indebted to my instructors.

By angelo f

•

Dec 11, 2019

This course was exponentially better and more informative than the previous. Thank you!

By FABIYI O

•

Aug 19, 2019

Great course!!!

Really thorough with adequate examples to understand the concepts needed

By Emre E

•

Aug 3, 2019

Simple breakdowns of hard concepts and building intuition from ground up. Great Course!

By Afiq S

•

Feb 24, 2019

Though a little more complex for a Python beginner like me, I find it easy to follow :)

By David A

•

Oct 15, 2018

Excellent information on improving networks. Real ground up understanding very helpful.