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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

56,647 ratings
6,498 reviews

About the Course

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

Top reviews

Oct 30, 2017

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

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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6301 - 6325 of 6,427 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Vishnu

May 6, 2020

I wish the course material on Tensorflow was updated to Tensorflow 2, but it is also nice to know what happens under the hood. I also wish there was some programming assignments in which we could tune some hyperparameters and visualise the difference between selecting diferent values.

By Akshaya R

Jan 12, 2020

Good explanation of hyperparameters and optimization in DNN. As a beginner to tensor flow, I felt it hard to debug the tensor flow assignment. It would have been easier if the assignment included validation of each function before building the complete model.

By Salim S I

Aug 12, 2018

Would have liked programming assignment in python to understand the various initializations and optimizations. Although tensorflow introduction was good, It felt like being left stranded without a python assignment to cement the things learnt in the class.

By Brian W

Oct 17, 2019

The lectures are good and informative. However, the programming assignments are hard to learn from - an unhelpful combination of too easy and too obscure, so that it's hard to believe I'm developing skills that will help me program such things myself.

By Kevin J

Aug 1, 2020

Ich hätte mir gewünscht, dass Hyperparameter Tuning tiefer behandelt worden wäre.

Anstelle eines randomisierten Ausprobierens hätte ich mir mehr Erfahrungswerte gewünscht, wie man situationsabhängig Netze konstruiert und Parameter wählen sollte.

By Andrew W

Nov 2, 2019

The material is very well and intuitively explained. I am disappointed with the assignment. It seems to be based on older versions of Tensorflow, and seems a bit outdated. This becomes very clear if one tries to run the assignment locally.

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 4, 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 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.