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

4.9
stars
57,409 ratings
6,599 reviews

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

AS
Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

NA
Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

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6426 - 6450 of 6,525 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Aniruddh B

Apr 15, 2020

Docked one star because of using Tensorflow 1.4 instead of 2.0. Docked another star because I found the course content less interesting than the first course.

By Kishore K

Sep 17, 2018

Some of the videos are very abstract and needs a bit of mathematical intuitions. These intuitions are best obtained by calculations rather than a lecture :)

By Yazid H

Oct 12, 2019

A bit too theoretical for my taste, lacks practical homework and getting our hands dirty. Really appreciated the final week's structure and topics.

By harmouchi m

May 6, 2018

ike usual andrew ng perfect explanation simple go to essential stuff.

the minus points some troubles with notebook

big thanks for andrew ng's team.

By Marco B

Apr 20, 2020

There are errors on some exercises (adam of week 2) still unsolved after over 1 year (found same error reported on the forum/discussion)

By Christian K

May 22, 2018

The lecture videos are good but the assignments are not that useful as they provide th answers within them and are somehow repetitive.

By Pavel K

Aug 3, 2019

Lectures are good. Programming exercises are too easy. Too mechanical, no much thinking required, à la "fill the gaps" exercises.

By Rupamita S

Jun 1, 2020

I would give five starts if not for that grade error issue. I hope it gets resolved for good. Otherwise. Great course as usual.

By Carsten B

Jun 9, 2020

Interesting, but not nearly as good as the first one. Disjointed topics, unconnected exercises made this less digestable.

By Tan K L

Jan 25, 2019

I think more should be done regarding the TensorFlow framework with more explanations given to what the functions did

By Moustafa A M

Dec 9, 2017

Lake of practice, Lake of intimations with good examples

Less in Ternsorflow don't know how to implement and deploy it

By Mohammad E

Aug 14, 2020

The course and the material are great. However, the codes in the labs have serious problems which should be solved.

By Lucas N A

Mar 6, 2020

Really helpful advises. I felt it was too focus on the implementation side but I liked the intuitions parts better.

By Rishabh G

Apr 28, 2020

Week 3 of the course does not have a practice problem for batch normalization. Wanted to implement it and learn.

By Ramachandran C

Oct 6, 2019

I found the video lectures useful to understand the concepts, but the programming exercises are over-simplified.

By Carlos V

Jun 20, 2020

Would give more stars if the final assignment used Tensorflow@ and not an outdated version that is not in use.

By Pranshu D

Mar 6, 2018

More tensorflow related tutorials should have been there. The lectures turned a little boring and redundant.

By Adrian C

Nov 30, 2017

So far, I think this course is weak on theory, seems rushed and should provide more in depth lecture notes.

By Vincent D W

Oct 26, 2019

Encounter Error in the final assignment, cannot complete the model, but the grader gives 100/100 anyway.

By Amit C

Feb 1, 2019

I wish the course mentors were more active on this course makes it a bit difficult to clear doubts

By Laura L

Mar 22, 2018

It does not make you think of the problems, just fill in the gaps. First course was better.

By Mostafa A E N

Jul 29, 2020

Programming assignments are too easy and the answer is already given before the question.

By harsh

Jun 28, 2020

Tensorflow is not at all user friendly, I'm sure better alternatives would've been there.

By Aviv D

Apr 25, 2020

I recommend adding a summary page at the end of each week to make sense the mathematics.

By Tanurima M

Jul 4, 2020

The course is outstanding just the tensorflow library should be taught more in details.