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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
63,224 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

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

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1001 - 1025 of 7,258 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By prashant p

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Jan 23, 2020

The course content is of adequate depth and sets a good base for us to start applying DL in our projects. A project component can also be added to make it even better

By Devkul S

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Jul 2, 2019

This is the most important course to know in details about hyperparameters, epochs, regularization and opitmization. This course taught me in deep about improving DNN

By Michael R

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Mar 10, 2018

Continues right where the first module stopped. Really like the sessions approach and the exercises and quizzes are well documented to serve as future 'cheat sheets'.

By Shvetal P

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Feb 27, 2018

Nicely designed course with perfect explanations and guidance for learning and applying Deep Learning and to develop Deep Neural Network based applications very fast.

By Sintyadi T

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Feb 14, 2018

THe course is not a course where you will just go along with the hints... You need to do lots of logical thinking and also a bit of googling to understand what to do.

By yixin@couresa

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Jan 3, 2018

It is very clear that videos and homework in the course are carefully crafted and carefully handled , and again thank Coursesa for providing such a good course for us

By Benjamin H D

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Sep 10, 2017

Really useful content, describes multiple techniques to significantly improve NN training & implementation. Certainly useful for making efficient & effective networks

By Deleted A

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Aug 21, 2020

I love the way Andrew teaches. I am very grateful to learn so many things in deep learning from this course on optimization and my first small project on tensorflow.

By Sayantan S

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Jul 28, 2020

This is really a very good course to do after learning the theories about neural, I would have loved it even more had the tensorflow material had been slightly more.

By Amit K

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May 28, 2020

Learned very important aspect of tuning hyper-parameters in neural networks. It helps in better understanding how neural networks works and how we can optimize them.

By Saravanan S

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Jan 19, 2020

The Author(s) have made that the hard concepts are simplified to understand to maximum extent. I thank and appreciate the way Andrew NG has articulated the concepts.

By Anh N

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Jan 16, 2020

The professor helps me to learn many new, fantastic Deep Learning algorithms and concepts like Exponential Weighted Sum, Momentum Gradient Descent and Adam. Amazing!

By Simon W

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Oct 14, 2019

This course was great to build up deep learning intuition and turbocharge existing experience. Learn what to do when things don't go to plan as well as when they do.

By Florian K

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Jan 20, 2018

This is another of Ng's brilliant courses on the subject of neuronal networks. It is probably the best of such courses of such kind. I have learned a lot. Thank you!

By 刘传明

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Dec 5, 2017

Course taught by Professor Ng is always cool! I really learned lots of things on Deep Learning, especially on hyperparameter tuning, Regularization and Optimization.

By Louis-Marius G

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Sep 24, 2017

Once again prof. Ng delivers on a course with the perfect content and the perfect pace. His well thought out approach to the material makes going thru this a breeze.

By Ita C D

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Sep 19, 2017

great course. very helpful both the lectures and programming exercises. Reading Depp Learning textbook along by Goodfellow et all helps to broaden the understanding.

By 深度碎片

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Sep 1, 2017

If you have taken a few Machine Learning and Deep Learning courses online, you would know why Andrew's courses are the most friendly, engaging, and beautifully made.

By Sourabh D

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Aug 16, 2020

It is very helpful to learn about hyperparameters also last week you will get familiar with TensorFlow. I highly recommend this deep learning specialization course.

By Faiz

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May 28, 2020

Great Course with Top Instructors. Even if you are the beginner and not calculus expert, the detail and clear explanation from Prof. Andrew Ng. surely will suffice.

By Leonardo D

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Oct 1, 2019

I learned several optimization strategies as well as some regularization technics. It was also great to have got introduced in the using of ML specialized software.

By Hidayat u r

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Jul 24, 2019

This has been a great Course . After completing the course i am able to optimize a neural network by choosing the proper optimization and regularization parameters.

By Gourav S

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Jun 17, 2019

as with all Andrew's lessons, this was quite a nice learning experience. I am very slow in learning, and Andrew's explanations are absolutely a pleasure to revisit.

By James W

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May 4, 2019

After taking course #1, This course really made it all concrete. The lectures were "spot on" and although challenging, it was a lot of fun working through the labs.