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
63,175 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

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.

Filter by:

2101 - 2125 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Jeffrey W

•

Nov 11, 2019

Good course

Some difficulty with programming assignments, because errors are difficult to debug

By Mitra T

•

Sep 1, 2019

this is the best like the course 1 and I am realy eager to pass the rest of this specializtion

By Takehiro M

•

Oct 8, 2018

I learned theory of essential technique to get good performance using Deep Learning.

Thank you!

By Carlos F P

•

Aug 16, 2018

Excellent course that provides some under the hood details for running NN. Highly recommended!

By Kartikeya P

•

May 24, 2018

Clearly explains optimization algorithms and techniques to improve neural network performance.

By Gopal J

•

May 16, 2018

learnt how to tune neural network. Now I can say I have a good understanding of hyperparameter

By Gianfrancesco A

•

Nov 17, 2017

Very good explanations about the basics of setting up a DNN and make it work in the right way!

By Michael S L

•

Nov 11, 2017

Terrific. Well-paced, programming assignments are good balance of programming chops and math.

By Max R

•

Oct 28, 2017

Great continuation from the first course - A deeper introduction to tensorflow would be useful

By Alexey S

•

Oct 22, 2017

This is great class. I strongly recommend it to every newcomers in the field of Deep Learning.

By James M

•

Oct 9, 2017

Some of the materials were very challenging and intriguing, and the course was well organized.

By Jian W

•

Oct 15, 2022

this course teaches practical skills with clear notations and understandable math expressions

By Francisco C

•

May 5, 2021

Un muy buen curso para entender a fondo los Hyperparametros de las redes neuronales profundas

By Dinesh J

•

Apr 29, 2020

Thank you Andrew for making everything easily understandable, I appreciate your explanations.

By MAYANK C

•

Apr 23, 2020

Andrew Ng explains the maths really well and that helps a lot when you start with Tensorflow.

By Di C

•

Mar 20, 2020

Love the course! Definitely need more efforts in digesting the materials, but so far so good!

By Bong M K

•

Mar 9, 2020

It's good change to me to learn hyperparameter tuning and deep neural networks understanding.

By George

•

Jan 26, 2020

the course was very intuitive, even for some who didnt have any robust computational algebra

By Yini Y

•

Jan 19, 2020

A lot of details and instructions are provide in this course. The practices are super helpful

By David S

•

Oct 10, 2019

Andrew NG is one of the best teachers I'll ever had. He convert difficult things to easy ones

By Ismael B

•

Jul 8, 2019

great instructor, great course content. Would recommend to anyone looking into deep learning!

By Matt L

•

Nov 18, 2018

Enough detail to get an in-depth exposure, but very doable assignments with a lot of support.

By Edgar O

•

Sep 4, 2018

Great course and probably the most useful as limited free materials exist online. Thank you !

By Shruti B

•

Jul 22, 2018

The course was pretty useful in providing overall insight about improving DNNs. Great course!

By Sajin P

•

Jul 4, 2018

Excellent course content to learn parameters tuning and speeding up deep learning algorithms!