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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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1701 - 1725 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By PATEL H V

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Nov 27, 2020

This course helped me to understand many concept thoroughly . Also, provided practical knowledge of each concept.

By Teja S

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Oct 12, 2020

It is pleasure doing the course, it has beatifully curated lectures for fundamental understanding of the concepts

By ANKIT M

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Jul 24, 2020

My whole expectation from the course meet! Thanks Andrew NG sir and Coursera to provide such an excellent course.

By Arpad H

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Jul 6, 2020

I liked it very much :-) At least I used tensorflow and I understand what happens in it. I like Python very much.

By Lokesh T

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Jun 30, 2020

It is such an amazing course. I learned a lot of thing during that entire course.The explanation is very awesome.

By Sudarsaan A

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Jun 24, 2020

As always Andrew Ng's teaching is amazing which never fails to give us a intuitive understanding of the concepts.

By Ayan C

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Jun 2, 2020

Exceptional course with a lot of in-depth look into the various hyperparameters used in deep learning algorithms.

By Tan W H

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Jun 1, 2020

A really great course that explains most if not all the tunable hyperparameters in a typical deep neural network.

By MOHAMMAD A U

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Apr 3, 2020

Excellent course. Pretty much in-depth knowledge provided. Thank you for the course.

Special Thanks to Andrew sir.

By SEBASTIAN M G S

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Mar 8, 2020

Very interesting and good implementation in the Jupiter notebook.

However, Tensonflow introduction is very vague.

By vanraj

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Dec 24, 2019

After completing the first course of this series, I feel very confident in applying Neural Networks in my domain.

By Jordan S

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Sep 11, 2019

A great introduction to tuning neural nets. Exercises were extremely useful in explaining the techniques further.

By Celia C

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Mar 27, 2019

Hope the tensorflow homework can be more clearly instructed. And hope there were more tensorflow part of homework

By Varun N

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Mar 27, 2018

Very useful course which gives insight into the nitty gritty details of the practical aspects of neural networks.

By Mansi G

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Dec 25, 2017

This course was much more challenging than the previous one. Go into it prepared to put in a lot of extra effort.

By Bruce D

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Dec 10, 2017

Fantastic course, really jumps into important details for practical programming and implementing neural networks.

By Manish Y

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Dec 3, 2017

Good course for understanding optimization of neural networks and their implementation. Introduces to TensorFlow.

By Deleted A

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Oct 26, 2017

Recommend! I feel much better with this course than the first one, probably because I get more used to this area.

By Tan S P

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Sep 29, 2017

The last programming exercise is really tough if you're not so good at Tensorflow. So you're better be good at it

By C-y T

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Sep 9, 2017

Dr. Ng shares his programming experience, provides easy and intuitive explanations of some complicated processes.

By Immanuel D

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Oct 25, 2023

Amazing for Absolute beginners who want to learn about working and significance of Hyperparameter optimizations.

By Robert W M

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Aug 12, 2022

An excellent resource for learning about how different optimization algorithms really work. Thank you Andrew Ng!

By Manika J

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Dec 3, 2021

This is one of the best courses to develop intuitive understanding of Deep Neural Networks along. Simply amazing

By Mina H

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Oct 6, 2020

Andrew is a great instructor. I've learned so much about hyperparameters in this course and I'm really grateful.

By Tanay A

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Jun 29, 2020

It's a really great course. A must even if you know the basics, as it really adds value to what you already know