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

4.9
stars
63,295 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

AM

Oct 8, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

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.

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2351 - 2375 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Mohamed S

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Dec 31, 2020

I would like to take the opportubity to thank Deeplearning.AI team for the great work

By Sujan R

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Oct 26, 2020

Very good course and as always, Andrew Ng does very good job and explaining concepts.

By Zhongtian Y

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Aug 24, 2020

I think I got used to Andrew's Class and it become much understandable once you adapt

By Jatin G

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Jul 9, 2020

The comments in jupyter notebook are very well written to explain the code and tasks.

By Varsha G

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Jul 6, 2020

It would be better to have more assignments where we have to do everything on our own

By Zack K

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Jun 11, 2020

Great job at explaining hyperparameter tuning, mini-batch gradient descent, and more!

By Salehin

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May 21, 2020

It is a remarkable course for a beginner to learn optimization and code in TensorFlow

By Praneetha V

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May 4, 2020

Thank you Mr. Ng, for these great insights and intuitive understanding! Learnt a lot!

By MD N I

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Apr 10, 2020

In one sentence, I can say its a really well organized and exceptionally well course.

By AMIT P

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Apr 3, 2020

Well explained and the programming assignments are the best. Learnt a lot.

Thanks Sir

By harshavardhan p

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Feb 29, 2020

I HAVE LEARNED HOW IMPORTANT HYPERPARAMETERS TUNING, REGULARIZATION AND OPTIMIZATION

By Rishabh S

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Dec 27, 2019

Great learnings from this course specially on the optimizations. Glad to do this one.

By Harish J

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Jul 22, 2019

Great Course on tuning hyperparameters. Addition of Tensorflow was great and helpful.

By Manuel N R

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Jul 7, 2019

Genial. ahora me siento mucho mejor parado para la implementacion de redes neuronales

By Yasiru B S P

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May 22, 2019

COURSE CONTENT WAS WELL DEFINED AND ORGANIZED. EXPLANATIONS ARE REALLY SMOOTH AS WELL

By vikash k

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May 2, 2019

Very well explained. Assignment covers almost all type of problems taught in lecture.

By Rafael A

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Apr 17, 2019

Excelente curso, recomendo fortemente, principalmente pela base matemática fornecida.

By Walker J

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Mar 19, 2019

Great course that has thought me a lot about building practical deep learning models.

By Bhaskar G

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Mar 12, 2019

I loved this course. It was very in depth and helped me understand a lot of concepts.

By MichaelXuan

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Feb 26, 2019

Nice descent course and it helps a lot for either my personal interest and my career.

By Bach T T

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Feb 1, 2019

It's great to know how to adjust hyperparameters and make my NN work more efficiently

By Vimal M

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Dec 16, 2018

Best course to understand the effect of different hyper parameters on model accuracy.

By yangbaoshan

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Aug 25, 2018

非常好的课程，吴恩达老师讲解的十分透彻，并且有非常好的，练习环境，对于巩固课程学习的知识十分有帮助，最后再次感谢吴老师团队的精心制作。感谢coursera团队的帮助谢谢。

By Arvind M

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Jun 6, 2018

Topic covered in this course will really help data scientist to improve ones DL model