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
63,238 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

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

JS

Apr 4, 2021

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

Filter by:

2451 - 2475 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Maximiliano A R F

•

Oct 11, 2020

Great course, a lot of techniques that improve your NN that is necessary to know.

By Harvinder y

•

Sep 26, 2020

very explicit course for hyperparameter tuning for practical application based DL

By Simin F

•

Aug 10, 2020

Andrew's lecture are vivid~ And the weekly assignments are really helpful for me!

By jagadish b

•

Jun 1, 2020

It was a very good course, with good explanation of each parameters in each video

By Amit R

•

May 24, 2020

The programming assignment should be updated. Pytorch framework can be used here.

By Satyajeet P

•

May 11, 2020

Brilliant undoubtedly, felt nice to get my first hand on experience on Tensorflow

By Lee

•

Feb 23, 2020

Provided a lot of insightful explanation to hard concepts from a intuitive level.

By Deividas S

•

Jan 18, 2020

Amazing teacher! Definitely recommend to people wanting to learn Machine learning

By Sadam H

•

Dec 4, 2019

I learned things that I did not know before. I am enjoying learning new concepts.

By Wilem

•

Nov 24, 2019

Finally a course that explains Adam Optimizer, and it's not a black box !

Thanks!

By Shahriyar R

•

Oct 11, 2019

Clear explanations and very solid exercises helped me to understand new concepts.

By Tsoi I

•

Aug 25, 2019

Very useful knowledge for understanding different parts of modern NN optimization

By Jacky

•

Jul 23, 2019

Simply fantastic. This second course of the specialization continues to amaze me!

By lalith S

•

Jul 10, 2019

learnt many practical aspects for DL hyperparameter tuning.Don't skip this course

By Luan G

•

Jul 7, 2019

In this course, I was able to make my knowledge of hyperparameters become deeper.

By saurabh h

•

Jun 26, 2019

Great course ! Lot of things covered.

Expecting more on the Tensorflow Framework.

By Vaibhav K

•

May 24, 2019

Nice course for getting an overview about hyperparameter tuning for deep learning

By Luis T

•

May 15, 2019

Great course, clear explanations and examples base on the real life applications.

By Pratibha R

•

Nov 19, 2018

Right course to learn working and implementation details of Deep Neural Networks.

By JONGHO O

•

Aug 13, 2018

It was nice lecture and I had learned about Improving Deep Neural Networks skills

By Gita D

•

Aug 1, 2018

Just excellent...many practical aspects of training a good model has been taught.

By Giacomo A

•

Jan 28, 2018

Very clear and systematic, goes through all the fundamental information one needs

By Ivan A

•

Jan 5, 2018

Very well organized course. It gives you a good introduction to this broad field.

By Jk L

•

Nov 10, 2017

Many benefites for me although i have been working in the CV and DL for some days

By LI M

•

Aug 24, 2017

It will be better if there are more tensorflow contenct and unsupervised learning