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

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.

Filter by:

2026 - 2050 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Liam A

•

Jun 16, 2019

Great at introducing key hyper-parameters, their importance, and the appropriate way to use them.

By Roronoa Z

•

Jun 14, 2019

The problems are getting more and more interesting :d

On to the next course in the specialization!

By Korobov P

•

Apr 28, 2019

Excellent! I've learnt about useful optimizations and some delicate things about neural networks.

By Ravikant C

•

Mar 28, 2019

I really enjoyed doing this assignment. A perfect combination of hands-on and concept discussion.

By Kirk B

•

Jan 17, 2019

Andrew Ng is hands down the best teacher in this space. Excellent lectures and a well run course.

By Akhil K

•

Sep 6, 2018

Course content is really good.

A more thorough introduction to tensorflow would have been helpful.

By Andrei V

•

Aug 14, 2018

Great as always! Really informative and the subjects are presented in an "easy to digest" format.

By Arthur B

•

Jul 19, 2018

Very informative, I liked the explanations as to how to approach fine-tuning your neural networks

By Mulong X

•

Jun 21, 2018

It would be better if there is more code could be edited my ourselves rather than just few lines.

By Rinaldo M

•

Jun 20, 2018

Good knowledge for improving our model and nice introduction to other framework in deep learning.

By Kishan

•

Jun 18, 2018

Rightly structured and very well organized just after a beginning introduction to Neural Networks

By DrDee

•

Apr 23, 2018

Prof. Andrew Ng is fantastic at explaining complex ideas in a systematic, easy to understand way.

By Roxana N V

•

Sep 30, 2017

A great course to a deep understanding of hyperparameter tuning, regularization and optimization.

By Jakeer H

•

Jul 4, 2022

I have enjjoyed this course while writing the code using Tensors. Thanks to all the instroctors.

By Tarandeep S

•

Jan 2, 2022

Intution are really helpful in understanding the topic and the way Andrew explains is awesome!!!

By DEEPAK P

•

Oct 19, 2021

I find this course a fun learning as i learned about hyperparameter tunning and tensorflow also.

By Amin

•

Jul 15, 2020

This specialization was one of my best friends during the pandemic, thank you so much Andrew NG.

By Manas P

•

May 7, 2020

Great explanation from a Great Person!

I will keep revising the content to get a better insight.

By Yunya G

•

Sep 3, 2019

This course is very useful for me. It helps me understand better some parts in the first course.

By Prasanth T

•

Jul 22, 2019

Very useful and programming assignments came in handy to revise and strengthen the understanding

By Johnson J

•

Mar 24, 2019

Awesome course! Andrew explained optimizers like RMSProp and Adam very clearly. I learned a lot!

By Georgy K

•

Dec 25, 2018

A bit challenging in term of number of ideas in such limited amount of time. Very useful anyway.

By Xin ( Z

•

Nov 30, 2018

Great course. I finally made it to learn TensorFlow before I can start some fascinating project.

By Jalaz K

•

Oct 19, 2018

Really Good Course. Provides better understanding to the hyperparameters & their tuning process.

By Zheng H

•

Aug 4, 2018

I like the content of the classes of this week.

The teaching style of Mr Ng is very interesting.