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

4.9
stars
63,522 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 9, 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

DH

Apr 27, 2020

Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.

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6926 - 6950 of 7,292 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Santosh P

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Mar 23, 2020

Excellent course. Bit tougher than first course

By Kousik R

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Jun 12, 2019

There are so many grader problems please fix it

By Abhijith A

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Oct 2, 2018

Good course, could have done more on tensorflow

By abiran r

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Jul 12, 2020

i learn a lot of things related to tensorflow

By Mike R

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Nov 2, 2019

Tensor flow should be explained in more detail

By Kullawat C

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Oct 2, 2018

Very great course on how to tune NN in details

By Harsha S

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Jan 23, 2018

Builds on fundamentals, which is always good!!

By Tiến H N

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Apr 6, 2021

The coding assignment is not challenge enough

By Paraskevas P

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Mar 30, 2020

More practical examples would be very useful.

By Aymen S

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Aug 13, 2019

Cours intéressant merci beaucoup Mr Andrew Ng

By Anna W

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Sep 13, 2018

batch optimization is good but not graded :-(

By Yiping W

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Jun 24, 2018

should provide more materials for tensor flow

By Abhishek A

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Nov 25, 2021

Tensor Flow could have been elaborated more.

By MD N F

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Feb 15, 2021

Concepts explanation was not up to the mark.

By Freddy A C F

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Jun 26, 2020

great now I understand Adam optimizer better

By 長谷川一輝

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Jan 9, 2020

I can understand concept of deep neural net!

By Bernardt D

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Jun 27, 2018

There were some typos throughout the course.

By Michael N

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Apr 13, 2018

Great but som explanations seems a bit wierd

By Karl B

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Oct 28, 2018

Tensor flow stuff could be better explained

By Mecrux

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Sep 4, 2018

Maybe should spend more time on tensorflow?

By Arnav D

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May 22, 2018

Best TensorFlow tutorial I have seen so far

By Sandor T C

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Jan 29, 2018

too much hand holding, no struggle to learn

By John R G P

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Aug 20, 2020

Its necessary to actualize to tensorflow 2

By Paulo A V

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Nov 16, 2017

Nice complement to the first course on ANN

By Lina H

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Aug 4, 2022

I wish it had moe practical assignments.