Chevron Left
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
63,068 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

Invalid date

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.

YL

Invalid date

very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

Filter by:

3451 - 3475 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Bin P

•

Apr 4, 2019

Mathematical explanation of optimization concepts.

By Changik C (

•

Mar 20, 2019

Just like all other Professor Andrew's class, best

By Jimut B P

•

Feb 28, 2019

Just awesome course! Never learned so well before.

By Yash G

•

Nov 29, 2018

Amazing course gives useful insights for training!

By Mohd. F I S

•

Nov 15, 2018

Great professor Andrew is simply awesome as always

By Nagadeepa N

•

Nov 13, 2018

Very easy to follow instructions. Great learning.!

By Mahesh p

•

Jun 18, 2018

Good course and learned deep learning optimization

By ANKAN B

•

May 31, 2018

Amazing Course and will complete rest courses too.

By Joseph F

•

May 24, 2018

Step by step about essential work of deep learning

By Ankur N

•

Apr 7, 2018

Best course for Deep learning tuning, optimization

By Sukegon

•

Mar 6, 2018

I can get lots of intuition! Thank you very much!

By Jianbin L

•

Jan 16, 2018

not enough assignments, but nice and simple enough

By Chao ( Z

•

Jan 15, 2018

Helpful and time-saving to get hang of this stuff.

By JUNGHOON C

•

Nov 19, 2017

Quite difficult session but very meaningful course

By Krzysztof R

•

Nov 14, 2017

Excellent, practically oriented course. Thank you!

By AlfredO

•

Oct 26, 2017

Very well presented and the assignments are great.

By Ariel S

•

Oct 5, 2017

Excellent course! Thanks to instructors and staff!

By Arushi A

•

Oct 2, 2017

The pace and content of the course is brilliant :)

By Prakash C C

•

Sep 22, 2017

Worth Studying. Very useful for practical insights

By Yixing Z

•

Sep 14, 2017

Thanks Andrew and your team, really help me a lot!

By Clément N

•

Jul 15, 2023

Excellent course! Prof Ng, is such a good teacher

By WÅ‚odzimierz J

•

Jun 8, 2021

Good course. Nice mix of knowledge and exercises.

By 胡泽天

•

Nov 23, 2020

So glad I can learn so many frameworks operations

By Fuad A

•

Oct 10, 2020

It's a pretty interesting and well taught course.

By VADDANAM G

•

Sep 12, 2020

Very well - taught by Andrew, thank you coursera.