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:

4151 - 4175 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By DUTENGJIE

•

Nov 19, 2017

老师上课非常耐心同时富有激情，配套的测验题和编程练习都很容易上手

By vishwanathan r

•

Oct 29, 2017

A great continuation to course 1

By Alex M

•

Oct 8, 2017

The best course among all others

By Felix H

•

Oct 5, 2017

Informative, Concise, Practical.

By shihiko

•

Oct 1, 2017

I enjoyed this course very much.

By 王卓

•

Aug 27, 2017

Excellent course! keep learning!

By Abdillah F

•

Nov 10, 2020

The best deep learning course!!

By Dirk P

•

Nov 8, 2020

Great pedagogical introduction!

By Sanket K

•

Oct 14, 2020

Excellent Course Well organized

By purvak p

•

Oct 10, 2020

Good content. Nice explanation.

By christson h

•

Sep 24, 2020

Thank You for Such Great Course

By aseel .

•

Sep 10, 2020

thanks for this valuable course

By ROHIT R K

•

Aug 29, 2020

Excellent course to start with.

By Paul R

•

Aug 24, 2020

Concise, but very to the point.

By Ajay G

•

Jun 6, 2020

Excellent teaching methodology.

By Bhaskar J D

•

May 25, 2020

Excellent Content to understand

By Dr. V V R M R

•

May 7, 2020

very good inputs for TensorFlow

By Edward M

•

Dec 22, 2019

Another great Andrew Ng course!

By MURALITHARAN S

•

Dec 13, 2019

Nice Work, Good Learning For me

By 楊惇昱

•

Nov 8, 2019

Thank you. It's a great course.

By Bahalul K

•

Nov 8, 2019

it is very helpful to my career

By Habibur M

•

Nov 4, 2019

Easy to understand. Thank you..

By Brendan F

•

Sep 2, 2019

Great explanations and examples

By Harish M

•

Jun 8, 2019

Very good lectures by Andrew Ng

By 김화겸

•

Apr 27, 2019

Andrew ng.... i love so much...