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

4.9
stars
63,175 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

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.

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

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2801 - 2825 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Madhav P

Jul 25, 2020

Gained some pretty strong basics in Optimization algos, tuning etc...

By 柳子豪

Jun 10, 2020

A nice combination of theory and hands-on practice for improving DNN.

By Michael Y

May 23, 2020

Another excellent course, well taught and great programming exercises

By Manthena S S R V

May 17, 2020

It was an excellent course, I have learnt a lot through this course..

By Surendar A

May 16, 2020

Thnaks Andrew!! You keep on inspire us through your indepth knowledge

By Виктор В К

May 11, 2020

Отличный курс. Очень познавательный. А преподаватель просто отличный.

By Raeed A

May 7, 2020

Very well detailed and interesting course. develops a lot of interest

By Marcelo F

Apr 30, 2020

A good overview on hyperparameters optimization. Good intuitions too.

By Azamat S

Mar 19, 2020

Great techniques on how to improve the performance of your algorithm!

By cristian m

Feb 7, 2020

Fue un curso muy interesante e enriquecedor, Very much thanks for it.

By Reetu H

Dec 13, 2019

Got a little challenging but helped in learning alot of new concepts.

By Meera J K

Nov 6, 2019

amazing course. Andrew Ngs teaching and course material is very good.

By Farzam T

Nov 2, 2019

It was one the best experiences I had with coursera and learnt alooot

By Huzaifa A

Jul 25, 2019

Good course for learning about DL projects and programming frameworks

By Chen H

Jun 19, 2019

Great course, easy to understand with enough programming instructions

By Ryan L

Jun 8, 2019

Shallow dive in practice. Great starting point! Thank you, Andrew !!!

By Krystian P

Feb 12, 2019

The homeworks (programming assignments) are a little bit an overkill.

By Loay W

Jan 10, 2019

I liked the Framework choice as TensorFlow and the project was nice!

By RAJAT K B

Dec 21, 2017

Excellent lectures on hyperparameters and optimization techniques :-D

By Trong-Tin D

Dec 4, 2017

Give some good practices in optimizing neural network implementation.

By Sunil D

Nov 6, 2017

Right balance between details and speed at which course is conducted.

By Gong Z

Oct 12, 2017

wonderful lecture! Gained so much from this lecture, thanks you guys!

By Vivek P

Oct 3, 2017

Learnt a lot in the course. Nice to be introduced to tensor flow too.

By Gabriele T

Sep 29, 2017

A wide and deep explanation of the most important improvements for NN

By Harry P

Sep 20, 2017

Looking forward to Convolutional Neural Networks and Sequence Models.