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
62,961 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

NC

Invalid date

Yet another excellent course by Professor Ng! Really helped me gain a detailed understanding of optimization techniques such as RMSprop and Adam, as well as the inner workings of batch normalization.

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:

6901 - 6925 of 7,225 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Mayank J

•

May 13, 2020

I expected it to be in TensorFlow 2.0

By jyning

•

Dec 3, 2017

感觉作业设计的很好，可以不需要太好的编程能力就能完成，还能加深多算法的理解

By Y C

•

Jan 10, 2021

tensor flow could be upgraded to 2.0

By Merouane B

•

Jun 16, 2020

it was difficult somehow but awesome

By Yogesh K

•

May 28, 2020

Update to TensorFlow 2.0 is required

By Krupal b

•

May 24, 2020

Some model are not understood deeply

By Gerald B

•

Feb 14, 2018

Consistently challenging. I love it!

By Abhay V

•

Mar 27, 2022

tought at times. but great overall.

By Hans N

•

Apr 4, 2020

suggest to update to tensorflow 2.0

By Nguyen B L

•

Nov 19, 2019

excellent & quite challenge course!

By Sajal J

•

Oct 28, 2019

Very good course.highly recommended

By Teodor C

•

Feb 13, 2021

tensorflow1 instead of tensorflow2

By Shiva K

•

Aug 23, 2020

nice one, but video quality is low

By SAID B

•

Mar 15, 2018

It's a very helpful course.

thanks

By Vitaliy

•

Feb 28, 2018

Was nice but something is missing.

By Lilith S

•

Nov 4, 2021

the code is not working sometimes

By David B

•

Oct 5, 2017

W

e

e

k

3

e

x

e

r

c

i

c

e

c

o

u

l

d be improved

By Julia W

•

Dec 18, 2023

Videos are of poor audio quality

By Vincent L

•

Jul 16, 2020

Interesting and tough to finish.

By Lenny F

•

Sep 28, 2019

Would like to have more practice

By John M

•

Apr 4, 2019

TensorFlow needs more explaining

By Sam M

•

Apr 28, 2018

Some errors in jupyter notebooks

By ccbttn

•

Oct 8, 2017

last assignment need improvement

By Julian F

•

Sep 30, 2017

A very practical hands-on study.

By San Z

•

Jan 23, 2021

Tensorflow part is not that ok!