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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

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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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6601 - 6625 of 7,257 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Alexander

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Mar 9, 2020

I would like to learn the V2 of TensorFlow. Except that. exceptional course. I love Andrew's teaching!

By LEO L

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Jul 30, 2019

All is good except the submission part, sometime return submission failure without specifying a reason

By Deleted A

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Jun 22, 2019

Great Course ! I learned a lot, but I would have preferred another Framework though (like Pytorch) ...

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.