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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

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1676 - 1700 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Yuguang I

Dec 18, 2018

Andrew makes a mysterious subject so transparent. It is so calming to listen to his voice and understand the magic.

By Akash G

Aug 11, 2018

Very clear explanation of all related concepts along with Introduction to tensorflow framework. Very useful course.

By Gökhan

Dec 2, 2017

Very good course with a very good teacher. Understanding the mechanics behind all of this is very important for me.

By Christian B

Sep 24, 2017

This course presented some valuable improvement techniques for neural networks in a compact, understandable manner.

By Zhiyang W

Aug 21, 2017

Very amazing machine learning course, focusing on the very important and useful skills in training neural networks.

By Gopal R

Aug 16, 2022

Really thankful for this well structured course with full of practical and insutry insights from Andrew and team.

By Mohamed H

May 16, 2022

Thank you for this well-structured course. I have only one suggestion which is to increase the number of exercises

By shubham k

May 23, 2020

This is an awesome course than the first one. Thank you Andrew Ng for giving such wonderful content. Thanks a lot.

By ADITYA D

May 17, 2020

The course was very good and fully covered all the concepts and also had assignments for practice of the concepts.

By Lovepreet S

Apr 19, 2020

It was a very good experience to learn about Tensorflow and Tuning Hyperparameters and Using Deep Nets effectively

By MADISHETTI S

Apr 18, 2020

Balanced material having math and programming parts equally weighted. Enjoyed the lectures through the course work

By aditya m

Mar 7, 2020

Very helpful as it gives insights to many things that could not have been possible to gain by just reading a book.

By Isaac T

Oct 6, 2019

Excellent module for understanding the mechanism and insights on tuning hyper-parameters for Deep Neural Networks.

By Петро Г

Sep 16, 2019

I really enjoyed this course. There are a lot of great ideas to improve your learning system! Thanks Andrew a lot!

By J L

Jul 9, 2018

The comments expected results in the last assignment needs update. The errata has all of them though.Thanks a lot.

By mohamed h

Feb 8, 2018

Very good content and explanation. however, I think the programming assignment need to be more challenging. Thanks

By 艾宏

Sep 24, 2017

It's so good for me to go deep into Deep Learning theory and practise. Andrew and his teammate work hard on this.

By Xiangyu G

Sep 4, 2017

Great Course! Andrew always knows what to focus and every word from him is meaningful, I've learned a lot, Thanks!

By Ankesh K P

Aug 27, 2017

Great content. Helped to clear concepts of very in-depth hows and whys i had been looking for a long time. Thanks!

By Willy N

Aug 24, 2017

awesome material. well explained concepts on hyper-parameter tuning batch normalization and programming frameworks

By Noah W

Aug 16, 2017

This course is a bit difficult.But the lecturer explained in great detail.I have learnt a lot.Thank you very much!

By Shallom M

Jan 1, 2022

This course has been wonderful. I learnt alot and the insights into the theoritical side of things was top notch.

By Matt G

May 27, 2021

Good follow up course to the first course. Begins to get into the practical aspects that surround neural networks

By Kiril P

May 13, 2021

Every ML engineer should know how to speed up learning process. This course was extremely useful and interesting.

By Guru P B

Mar 28, 2021

very impressive and includes a lot of things, it would be better if there is a case study to show all the tuning.