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

4.9
stars
63,224 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

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

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6426 - 6450 of 7,258 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Hanqiu D

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Aug 10, 2020

Great course and great teacher. The skills in this course is very practical. But I think the assignment should use tensorflow version 2 instead of version 1

By Zach Z

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Mar 26, 2020

Learned a lot about tuning and different frameworks. Definitely math-intensive and more of a brief overview than a deep dive of these techniques and tools.

By Nilakshi R

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Dec 14, 2019

improving Deep Neural networks :Hyperparameter tuning,Regularization and optimization course was amazing! thank you so much coursera and Andrew Ng sir! :))

By Rohan P

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Sep 8, 2020

Similar focus should be given on programming assignments with a extensive discussion forums. Encourage learners to find functions themselves using google.

By Alex C

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Sep 24, 2017

Please offer a lecture note in detail instead of just ppt shows for each class video, not to mention that some are missing which is inconvenient to recap.

By Muhammad B A

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Jun 25, 2018

Great material and lectures. Would've preferred slightly more comprehensive exercises though, and more on tensorflow(any deep learning framework) as well

By Francois-Xavier

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Dec 17, 2017

The tensorflow programming assignment was a little too easy. It turned out to be more or less of a copy paste work without having to look at the TF docs.

By Masateru H

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Jan 7, 2021

Great intro to TensorFlow Framework. But the last programming assignment was still giving low percentage accuracy without any notable fault in the code.

By Behrad K H

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Jul 26, 2020

The content was perfect but last programming assignment was excruciating! But I thank everyone involved in making this course, it was unbelievably good!

By Flaviu V

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Apr 7, 2018

I feel like the second course was better then the first one. But there are a couple of typos in some assignments and the assignments are still too easy.

By Mark M

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Oct 30, 2017

The intro of hyper parameters was from mathematical point of view as good as the basics of week 1, however practical relevance becomes not really clear.

By Stephan W

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Sep 2, 2017

As always - excellent lectures by Andrew Ng. However, I think that the programming assignments tend to be a it too easy and a bit too much "copy/paste".

By Sepehr S

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May 10, 2022

Really enjoyed the course. Only suggestion is to talk about the programming side more in the lectures but overall I'm really happy Thank you very much.

By Nitin S

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Nov 5, 2020

In the last exercise of last week, we have to use TensorFlow v1 which was quite annoying if you already have learned tf v2 other than that great course

By Sergey

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Oct 6, 2019

I wish prof. Ng provided more intuitions into underlying math particularly why gradient optimization techniques help. But like it anyways, very useful!

By Anthony K

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Nov 8, 2017

Great material, few minor errors that need fixing throughout. Noted in forums. I expect this will improve as more take the course and feedback applied.

By Laurent P

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Nov 27, 2021

Week 3 programming assignment required notions not touched in the training or mentioned in the instructions. Required lot of time to find information.

By Hair P

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May 17, 2020

This course has to be updated!!!!! TF 2.0 is what we are using now, and especially for new users, it is important to start from the newest frameworks.

By Isaac S

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Nov 27, 2019

I missed in the course an explanation and possibly a programming assignment of different tuning algorithms, such as random search and Bayesian search.

By Rajeev D

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May 25, 2020

The coverage on the subject was adequate but it will really help to make a pdf supporting document to highlight the hyper parameter tunning approach.

By James D B

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Jun 22, 2019

Probably a little too follow your nose at this point in the specialisation. But none-the-less very good. Would give 4.5 stars if that were an option.

By Christoph S

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Mar 3, 2019

Still some flaws + inaccuracies + video sequences that should be cut out. I think the organizers should really do it as people are now paying for it!

By Teodor C

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Dec 28, 2018

Last Tensorflow assignment has some output typos and bugs when using operators like @ and +. Course was ok, but that assignment took me way too long.

By HongZhang

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Jun 13, 2018

Great course to deepen my knowledge after first course. However, I would like to access more programming exercise for practice. That will be perfect!

By Daniel E B G

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Aug 26, 2019

I think this course would benefit from a little more explaining. There are a lot of new concepts and some explanations were too quick in my opinion.