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

4.9
stars
62,825 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

XG

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.

JS

Apr 4, 2021

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

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6376 - 6400 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Wes H

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Feb 13, 2018

Some oversights in programming assignments and the week by week content is not very balanced in terms of effort/time spent. Otherwise, I would have given 5 stars.

By Julian K

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Jul 20, 2018

Introduction to tensorflow was kept a bit too short for my taste and the coding part was mainly copy pasting the instruction text from above, making it too easy.

By Harsh R

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Apr 21, 2020

Best course explains the whole concept in detail and taught by one of the most excellent ML teachers Andrew Ng must to understand the working of Neural Networks

By ShingB

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Apr 11, 2020

Thanks for providing the coursera for me to learn more about DeepLearning!But the web sometimes cannot open the jupyter, the net work is so unstable to log in .

By Keith S

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Oct 2, 2017

Great course - Some small typos in the programming exercises and the Tensor video felt a bit rushed (needs 1 more video or lengthier explanations would suffice)

By Thiemo M

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Sep 1, 2017

A big step forward to understanding how to tune neural network performance. Didn't learn all of this even through a couple of years of trial and error on my own

By KarenMars

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Dec 19, 2020

This is a very great course about the techniques of optimizing neural networks, for example, I have learned different methods to speed up the training process.

By Steven K

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Jun 24, 2022

- Lecture video was very educative and Andrew was a instructor

- I find the the coding assignment too easy - maybe because of the filling of the blank styling.

By Carlos R V

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Apr 30, 2021

The Tensor flow assignment is not clear why we don't use softwax activation at the last layer and why we use a binary cross entropy cos instead of categorical

By Israël T

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Jun 2, 2020

I suffered too much to handle Tensorflow since it's not well explained for beginners throughout the programming assignment. The rest of the course is awesome.

By irfan s p

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Feb 21, 2020

good course, but unfortunately different with network and deeplearning course, that has fast response mentor. But all in all the course is full with knowledge

By Kate S

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Mar 6, 2018

Excellent material! There was one error in the last assignment that cost me a lot of time. Please fix that. Otherwise, very useful programming assignments.

By SUNIL D

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Jul 7, 2019

Very Good Course to understand Step by Step

Hyperparameter tuning, Regularization and Optimization to improve Deep Neuaral Networks & Practical Assignments !

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".