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

4.9
stars
57,982 ratings
6,673 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

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.

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

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6476 - 6500 of 6,599 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Patrick P

Sep 21, 2017

The course notes don't lend themselves for use as reference materials. The programming exercises are spoon-fed. The material is more up-to-date than Andrew Ng's Machine Learning course, but that set a higher standard for online education.

By John D G

May 23, 2018

the lectures in this course seemed very packed and rushed, squeezing in a lot of content that felt skipped over instead of delving into the math a bit. The jupyter notebooks also have alot of errata that haven't been updated in a while

By Daniel T

Jul 2, 2019

The exercise although long was only related to the last section. There are some mistakes already reported by the students but no action yet. This is a good course do not ruin the reputation by some minor unaddressed issues.

By Sean J

Dec 23, 2019

It's a good lecture for background but the programming assignment is outdated. Tensorflow 1 is very uncomfortable and the assignment would have been a lot easier and intuitive if it was Tensorflow 2, Keras or PyTorch.

By Deeplaxmi

Apr 1, 2020

Thankyou for your great guidance sir. I am diploma student where we ain't taught much maths related to ML. I found difficult to understand mathematical equations. So i request you to upload a course on that too.

By Imad M

Nov 4, 2018

Week 1 and week 2 needs more examples of python programming in the videos. The videos for week 3 were a lot more interesting. Without the python implementation examples in the videos, the course can be very dry.

By Nikolay B

Dec 5, 2017

Lessons are nicely explained

Assignments should be more challenging. Same as first course, this one basically make you cope-paste instructor notes and just change variable names to pass all assignments.

By Caleb M

Jun 4, 2019

Enjoyed learning the concepts but it all seemed slow and tedious. It also seems like building up tensorflow throughout the weeks would be more useful then just piling it in the notebook at the end.

By Christopher D

Aug 1, 2020

It was a really good course, as I have come to expect when Andrew Ng is involved. The reason I only gave it three stars was for the sole fact that the version of Tensorflow is not up to the date.

By Riccardo F

Sep 24, 2020

Not enough about tensorflow, not a lot of extra information on hyperparmeter tuning, exercises simple and unchallenging. I like the instructor, but I wish we could get more challenging material.

By srinivasa a

Jan 9, 2019

its great foundational course but i feel with frameworks available the math behind it was little boring.Andrew NG is pretty good with explaining it well but sometimes felt it was too trivial

By Alexander V

Feb 25, 2018

Tests are very easy, and the programming exercises are very straight-forward - to the point where it is really obvious what to do. I could have learned more if both were more challenging

By Griffin W

Jun 29, 2019

Tensorflow was introduced in a very confusing way and most of the intuitions were not explained. Besides from lack of explanation for tensorflow, great course that complements the first

By Jorge G V

Mar 7, 2019

The lessons are good, the programming assignment has mistakes that have apparently been reported over a year ago and have yet to be fixed - there is no excuse for this to be the case.

By Aniceto P M

Apr 21, 2019

The course was well, but the last graded test was use Tensorflow and this requires a lot more knowledge than the last video which was an example of another completely different kind

By Peiyu H

Oct 12, 2018

Lots of error on the final exercise. It seems some errors exist from previous sessions already. Hope the teaching team will fix the errors and make learning less confusing for us.

By Jonathan A

Sep 10, 2020

The first course was really well put together. This one not so much. I learned a lot, but it seems that adding the TensorFlow exercise at the end of week 3 was an after thought.

By Ignacio L

Mar 3, 2021

dint like that the tensor flow that we used for the lab is an old one. Specially after I did the tensorflow specialization , the old version is nothing like the newer one.

By John D

Feb 13, 2021

The content was solid, but some of the labs seemed a bit buggy (getting full credit even though my code didn't run). I also wish the TensorFlow tutorial used TensorFlow 2.0

By Debjit G

Jun 19, 2020

The course was amazing as expected. But the quality of videos needs improvement. Also if programming part was explained in the videos then that would be great. Thank you.

By Sagar B

Jun 15, 2020

Too many issues with the auto grader system. Need to improve the know errors and save the time pf users. I spent more than 3 hours total just to fix the grader bugs.

By Yogeshwar j

May 24, 2020

It could have been more detailed and interesting. Compared to the first course of the specialization, This course's material didn't clear all the concepts clearly.

By Madhur S

Aug 4, 2020

Great course for a beginner like me. I wish however that sizing of hidden layers/units should have been addressed as it is very difficult to achieve the optimum

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 :)