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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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:

826 - 850 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sol S

•

May 3, 2021

Excellent introduction to practical aspects of applying deep learning. Demystifies so many of the core concepts and you gain valuable intuitions about many useful and practical methods.

By Tawfik O

•

Feb 8, 2021

This Course is well organized and geared toward beginners. I enjoys the content in each week's lectures. Hopefully I will explore more documentations to improve my skills in TensorFlow.

By W F (

•

Feb 2, 2021

Excellent practical material Teaches good intuition on how to train a model. Has answered many questions I've had. There is currently no other single source that addresses these topics.

By Kathiresan S

•

Aug 10, 2020

A solid introduction to hyperparameter tuning and setting up the optimization problem was given by the instructor. I was expecting a more brief introduction to the Tensorflow framework.

By coen h

•

Apr 11, 2020

This is a really good course after the intro course!! Even if you do not have phyton or AI experience like me, this course helps you through it and gets you to understand the principles

By Nilesh K S

•

Nov 2, 2018

The most exceptional course I have ever seen. Really I never thought that deep Learning will become so simplified with this.

Hats off to the mentors and a special thanks to Andrew Ng sir

By darghouthi m

•

Oct 27, 2018

i really liked this course,most concepts are nicely explained.

I just think that the part abourt the tensorflow framework should be more developped.

Thank you for this excellent material.

By Jielong

•

Apr 26, 2018

It is a good course. I have learnt a lot from all of the sessions and now I am getting more and more confident in building neural network by myself. BTW, I am ready to take next course.

By Charles Z

•

Dec 4, 2019

Dr Ng explained the fundamental things so clearly. In order to be a good developer on machine learning, you need to understand what is going on underneath the framework you are using.

By saad b s

•

Sep 29, 2019

Initially I thought this course to be a simpler course but eventually it turn out be a very conceptual and applied course. So this leads to a lot of learning. In fact Extreme learning!

By Parth P

•

May 5, 2019

This course is very useful for the computation of hyperparameters and Neural networks. This is helpful for the intermediate practitioner. I suggest for the go through this course once.

By Nash J

•

Apr 5, 2019

The teacher's explanations are in place and easy to understand. Arranged assignments are also very helpful in mastering the content of the classroom. In short, it's a very good course.

By Jonathan L

•

Dec 18, 2018

Recommended course for understanding the importance of hyperparameters in Neural Networks and understanding the structure of the optimizers used for training (gradient descent to ADAM)

By Pratap

•

Oct 26, 2018

Wonderfully designed course, I understood RMS Prop and Adam so well that I felt why other articles are so complex. Your explanation on exponentially weighted average is simply awesome.

By Brett B

•

Jul 20, 2018

Great at building foundations in deep learning, I have already worked with Tensorflow some, but now feel I have a better understanding of what the commands are doing behind the scenes.

By ANIRUDH S

•

Jul 10, 2018

Great course. I learned a lot, and the exercises although seems a little simple at times, really improves confidence in trying to implement and teaches some good conventions to follow.

By Juan G G

•

Feb 4, 2018

For the everyday practitioner of deep learning this course is definitely a must. Professor Ng explains the most important empirical techniques in the day to day use of Neural Networks.

By Ayush T

•

Jan 25, 2018

Just like the first course of this series, it is really a very good course. Everything was explained clearly. Not doubt. the highlight of this course is teaching style of Professor Ng.

By Marcel-Jan K

•

Nov 21, 2017

It's great to know how machine learning algorithms work, but I'm glad I can now also use them with TensorFlow. The practical assignments were very interesting, especially the last one.

By Animesh K

•

Oct 9, 2017

Great course that covers the optimization algorithms and advanced hyperparameter tuning concepts in greater depth. The last week also introduces the deep learning frameworks in details

By Antarip G

•

Feb 15, 2021

Its a very informative, in-depth course and nicely ties in with the previous course in this specialization. It demystifies the cloud of tuning parameters briefly discussed in Course1.

By Avdhoot A L

•

Jun 4, 2020

It was amazing course that showed the importance of optimizing the parameters which improve the performance of the algorithm to a great deal. A great course and an amazing instructor.

By Aravint A

•

May 5, 2020

Really good teaching and quizzes and programming exercises were of a decent difficulty level. Taught me a lot of things related to deep learning which are applied in various projects.

By anand k

•

Apr 2, 2020

The insights provided by Prof. Andrew are priceless. I sincerely hope that I get to go in such depths, as taught by him while implementing these algorithms in real-world applications.

By AF A

•

Feb 10, 2020

The last exercise for TensorFlow was the most fun of all the exercises! Explanations were good, and I still had the opportunity to google documentation to finish some of the functions