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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

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

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.

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6601 - 6625 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Qingyun W

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Jun 6, 2019

Some typos in the programming assignment is still not fixed (Mentioned in top posts in the discussion)

By Ryan M

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Oct 7, 2018

a very informative course, I was introduced to Tensorflow through this course... I absolutely loved it

By Dan C

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Feb 28, 2018

I had a bug in my compute_cost function that caused cost to spiral but the grader did not catch it....

By Yash J

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May 18, 2020

There should have been deeper explanation for the tensor flow section. Otherwise an excellent course.

By John C

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May 18, 2020

Great instruction on the fundamentals. Probably need to update to Tensorflow 2 or just teach Keras.

By Akshat D

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Apr 22, 2020

This was one of the amazing courses I've ever attended on Coursera. Kudos to Andrew NG and the team.

By sahil a

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Mar 11, 2020

week 3 : Tensorflow framework explanation can be much better otherwise the whole course is very good

By Lin Z

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Mar 28, 2019

interesting introduction about deep neuro networks with examples on how to use Tensorflow framework.

By Marijan S

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Sep 9, 2018

I learned very useful info, but the last programming asignment with tensorflow was a pain in the a**

By Sébastien C

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Nov 19, 2020

This is a good overview of optimization techniques. I think the exercises are sometimes too guided.

By Gopal K

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Jul 15, 2020

A lot things I got to learn.Also the worksheet were properly designed to clear any doubt if one had

By Apoorv A

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Feb 4, 2019

I think things could have been more difficult. Currently it is way to easy to pass the assignments.

By Sajal D

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Sep 13, 2020

an awesome course.....one can know more about deep learning from scratch by enrolling this course.

By Potnuru A

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Jun 18, 2018

This course provides more tips and ideas toward deep learning and introduces tensorflow. Worth it.

By Faniry R

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Mar 14, 2018

Best explanation ever! Exercises should be made available even without a possibility of submission

By Tirumala M

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Jan 23, 2018

Well explained the need of regularizations. Also python was best language to get assignments done.

By Siddhi V T

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Sep 19, 2019

An awesome course for someone who wants to learn how to tune the hyperparameters of their models.

By Alexey V

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Mar 18, 2019

Ran into bugs with some assignments, for example week 7 was not correctly calculating final model

By Tamás J

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Jun 14, 2018

Jupiter Notebook fails too offen! I had to close the window, start again, which is very annoying!

By Chen X

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Mar 27, 2018

It's fun they assume you know human error rate or optimal Bayesian. It's very rare in real world.

By Alejandro R

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Oct 26, 2017

I miss the end of video quizzes, but can't rate it lower than 4 because this course is excellent.

By Prasad D

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Jul 1, 2020

Some examples to be solved manually would have helped get a better understanding of the concepts

By Ayushman K

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Apr 24, 2020

Learnt a lot of new things. Only complain i have frmo this course is the use of Tensorflow 1.x .

By Digvijay R

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Jan 18, 2020

perhaps more practice of tensorflow is required. The tensorflow module also needs to be updated.