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:

3676 - 3700 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Alex T S

•

Feb 28, 2018

Comprehensive, clear, and engaging as usual.

By Uzair A

•

Feb 16, 2018

Very helpful and good learning experience...

By kingsleyhsu

•

Oct 27, 2017

very good,easy understand and help me a lot.

By Ryan S

•

Oct 11, 2017

Andrew is the best. Assignments are too easy

By José C B

•

Sep 8, 2017

Great material and didactic classes. Thanks!

By Ziqi L

•

Mar 25, 2024

Super great! Very systemetic and innovative

By 300_MEGHA S

•

Jan 18, 2022

perfect course for deep learning enthusiast

By JONATAN D P H

•

Jul 5, 2021

Genial!. Muchas gracias, aprendí muchísimo.

By Suraj P

•

Feb 9, 2021

Most important and unique course of series.

By Kostadin G

•

Jan 5, 2021

Fantastic way to learn/improve your skills.

By EL H E S

•

Jun 16, 2020

thank you very much for this amazing course

By Rima

•

Jun 12, 2020

Many important issues are discussed. Thanks

By Troy N

•

Jun 4, 2020

This is the special sauce to deep learning.

By Sadek N

•

May 24, 2020

Very helpful course.

Thank you Mr. Andrew Ng

By Avinash S

•

Apr 28, 2020

Its a must attend course, in deep learning

By Georgiy K

•

Apr 26, 2020

Надзвичайно приємний курс. Усім рекомендую!

By Jesus G

•

Apr 16, 2020

A very useful collection of tips and hints.

By Suresh K M

•

Mar 3, 2020

Thank you for sharing such a deep knowledge

By Abdul M

•

Jan 31, 2020

math part was quite difficult to understand

By Jaime G C

•

Dec 4, 2019

i like it, specially the part of tensorflow

By Chi Z

•

Jul 27, 2019

Good introductory material. Easy to digest.

By Bartosz G

•

Jul 23, 2019

Amazing as always. Andrew you are the best!

By Raj S

•

Mar 28, 2019

I cant stop myself to watch the next course

By Thor T

•

Feb 4, 2019

Many nice hints about hyperparameter tuning

By Naveen D

•

Dec 30, 2018

Andrew Ng is the God Father of AI Teaching.