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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

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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6776 - 6800 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sai K

Apr 23, 2020

There can be little more clarity in the Batch normalization topic.

By Corina S

Jan 13, 2020

Informative course, last exercise could be updated to Tensorflow 2

By Shubham K J

Aug 8, 2019

Grader is not performing well even though my outputs are matching.

By UJJAWAL S

Mar 2, 2019

Lecture were quite good. But the course assignments were too easy.

By Alberto S

May 20, 2018

By itself, not really a couse. It should be part of the first one.

By Muhammad W

May 11, 2018

few mistakes in course assignment but overall good course material

By Michael F

Apr 20, 2018

The programming assignments were too easy, otherwise good content.

By Siyu Z

Mar 19, 2018

A good course. I get familiar with the idea about hyperparameter.

By Carlos P

Feb 10, 2018

I would have liked to have more practice exercises about tunning.

By Yide Z

Dec 13, 2017

good course but there are some small bugs in video and exercises.

By Abhishek B

Aug 11, 2020

Goes bit into nity grity, which would be required in the future.

By Keith H

Jun 14, 2020

Always excellent. I wish I had had Andrew as a college prfessor.

By mat s

Mar 8, 2020

the material was good but the assignments could use improvements

By Omkar K

Dec 13, 2019

Really good insight into the inner workings of a neural network.

By Alexander K

Oct 12, 2019

Too less coding and practice exercises, thou the theory is great

By Efthimios K

Jun 13, 2019

Good but need letter recognition NN to understand what he writes

By Emanuel G

Nov 8, 2018

Tensorflow part was quite messy, but besides that, very helpful!

By K B

May 22, 2018

日本語訳があまりなかったので、英語がそこまで得意ではない初心者の人は勉強の順番の工夫が必要だと思う(自分はそれで乗り切りました)

By Akshat J

Jan 13, 2023

Good course, more research paper implementation can be included

By 张一帆

Jan 4, 2022

more code practice maybe is more better to master the knowledge

By Satyaki R

Sep 9, 2021

very good introduction to hyper parameter tuning and Tensorflow

By Anurag P

Apr 25, 2021

Nice lecture and basic definition and function in Deep learning

By Misael D C

May 22, 2020

I had some issues regarding coding, but other than that, great!

By Ananthan J

May 11, 2020

Need further explanation on the optimizer with gradient descent

By Miao Z

Apr 6, 2019

Great course, lecture is perfect. assignments could be improved