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
63,156 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

NA

Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

HD

Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.

the only thing i didn't have completely clear is the barch norm, it is so confuse

Filter by:

1651 - 1675 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Krishna T T

•

Nov 24, 2019

One of the best. Having been working with deeplearning for 2 years. Yet i have had some nice pointers in this course

By Seun O

•

Nov 13, 2019

There is a lot to digest in this course. As always, Andrew did a great justice to every element of the entire course

By Oscar R R M

•

Aug 27, 2019

Great course, perfect continuation for the machine learning course imparted by the Standford University on Coursera.

By Mohammed K A K

•

Apr 2, 2019

Concepts such as dropout, batch norm and exponentially weight averages are explained very well with good intutiions.

By Prafful P

•

Mar 31, 2019

Great Insights for improving performance of Deep Neural Networks, couldn't find any better resource other than this.

By Cynthia W

•

Aug 23, 2018

It was pretty tough, lots of content to understand, but the quiz and assignment really helped solidify the concepts

By Sumit K

•

Aug 14, 2018

Andrew Ng is the Best Instructor to have for deep Learning and related topics. I am impressed by his way of teaching

By Surya T K

•

Mar 11, 2018

Gives great insights about the importance of parameters in neural networks keeping in view the real time scenarios .

By Pradeep R

•

Feb 26, 2018

Short but excellent material as usual - and a gentle introduction to TF. Can't wait to learn more from Prof. Andrew.

By karan m

•

Jan 6, 2018

Explains the things in very good intuitive way and also introduces to basic maths so as to understand things better.

By KAUSHIK N

•

Nov 8, 2017

Very helpful material for Regularization and Optimization which are one of the most critical parts of Deep Learning.

By Ruoyu ( W

•

Sep 19, 2017

Very clear, easy to understand. The tutorial of Tensorflow and coding assignment are step by step, smooth to follow.

By Zhao Y G

•

Sep 14, 2017

It was fun and I learnt a lot in this course such as adjusting the hyperparameters and understanding the optimizers!

By Amit L

•

Apr 25, 2023

The course introduces great useful tools very clearly and the assignments contributes to the material understanding

By hossein r

•

Apr 28, 2022

It's really insightful. I wish it has more about Tensorflow and also you can choose between Tensorflow and Pytorch.

By Rajpurohit V

•

Oct 2, 2020

best course ever, awesome assignment I have created complete optimization algorithm from scratch awesome experience

By Agustin N

•

Oct 1, 2020

Great course! Easy to follow, and all the importants concepts and topics are covered in an intuitive way. Congrats!

By Aashish S

•

Jul 4, 2020

Well paced course. I liked the flow of the course especially since the topics were interrelated and organized well.

By Warley V

•

Jun 16, 2020

Great course! The intuitions, the first principles approach, the guided practice... A valuable way to learn indeed.

By Debadri B

•

Jun 8, 2020

Awesome course and excellent explanation of concepts. Another awesome course with best contents from Andrew NG Sir.

By Andrés O A

•

May 30, 2020

Andrew is great teaching and passing his ideas, the programming assignments are very useful.

Thanks for everything!!

By Harvey B C

•

Feb 9, 2020

One of the most helpful courses in the specialization, Gives you lots of good knowledge for training better models.

By 徐瑞宗

•

Sep 27, 2019

Amazing deep learning course which gives me so much inspiration about AI.Highly recommend to join it, will move on.

By Mohamed E

•

Aug 13, 2019

Powerful content in easy way and excellent assignments to make the knowledge more accurate and related to the work.

By Ali A

•

Mar 25, 2019

This course of Professor Andrew Ng is as excellent as all the others of him. When I think about AI, he is the best.