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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

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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6501 - 6525 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By George L

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Oct 24, 2018

it's good, but definitely not as good as the first course since Prof. Ng was not very clear on some of the concepts.

By Ruixin Y

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Apr 30, 2018

The course itself is great, but the notebook (programming assignment system) is not stable, it's annoying sometimes.

By Péter T

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Apr 17, 2018

Useful information, good intuition, but lack of formal results. More homework would improve the learning experience.

By Ashutosh P

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Apr 4, 2018

It was a great course. Really well taught by Professor Andrew Ng. Some "from the scratch" coding assignments needed.

By Suresh D

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Feb 28, 2018

I hated the tensorflow part though. Would have much preferred it if we could have moved away from jupyter notebooks.

By Francisco C

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Jul 24, 2018

Very good content overall. Very well explained and good examples. Many mistakes in the comments in the assignments.

By Abhinava K

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Dec 8, 2017

Content is good, but assignments are not interesting. Some application oriented assignments will be be encouraging.

By Julio T

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Sep 7, 2020

Very good course, all relevant and well explained. I think it just needs and update for working with TensorFlow 2.

By manish c

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Jan 23, 2020

Like all other andrew ng courses this course is also the best course to deep dive into neural network algorithms .

By Francesco P

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Feb 26, 2019

I would like to see more programming assignments. They are very well done and it'd be great to have more of those.

By Angad S

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Dec 13, 2017

I would really benefit from this course if more assignments are provided to try different data sets and scenarios.

By Christopher G

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Feb 23, 2024

Great course. Some guidance on implementing backpropagation with batch normalization would have been appreciated.

By Rahad A N

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May 13, 2020

Absolutely love the course and the way Andrew teaches us, though I have a little bit discomfort in writing codes.

By Emmanuel

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Mar 5, 2020

A little bit to theorical and with too many guidance at some points and not much at some other (for TF functions)

By Giovanni C

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Feb 11, 2019

I liked the course, but the explanation of tensorflow needs more propaedeutic introduction for a learner like me.

By Charbel J E K

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Jan 17, 2018

Really helpful ! Too much concepts to understand but only applying few in the course. I really liked this course.

By Jay R

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Dec 24, 2017

Good course to get familiar with hyperparameters and improving the neural networks. And cliff hanger was amazing!

By Mads E H

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Oct 26, 2017

Nice and practical. The assignments could go a step further in trying out different things to get better results.

By Jatin K

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May 23, 2021

Tensorflow exercise was not good , it could include some basics first. seems like only runnig it for no purpose

By Zechen Y

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Apr 12, 2020

The contents are explicit and adequate but I think It would be better if I could get more exercise about coding.

By Jayanthi A

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Apr 5, 2018

It was great course, however, I would have liked it to be a lot slower with more time being spent on Tensorflow.

By Idan H

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Feb 10, 2021

A great course!

I do feel that in order to become really good I now must apply the learned concepts myself soon.

By Johannes C d M

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May 27, 2020

Very well explained, but the Tenserflow explanation is shallow for those that have less programming experience.

By Dilip V

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Apr 29, 2020

This Course Helped me a lot in learning how to get best-optimized models by tuning Hypermeters.I really like it

By Joshua S

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Nov 13, 2019

A good course that provided more intuition on which models to work with and how to tune parameters effectively.