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Back to Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
stars
62,825 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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

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6601 - 6625 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Dongjin K

May 19, 2020

Hope to see the course materials and assignments get updated for tensorflow 2.0 in the future!

By Kasper J

Oct 1, 2017

Overall a very good course. However, I was hoping for more material on programming frameworks.

By Gleb F

Nov 8, 2020

Programming assignments are too easy, and don't help to grasp and think through the material.

By Shruti S M

Jun 5, 2020

Some more details & programming exercises about batch normalization could have been provided.

By Sanket D

Jun 5, 2020

It could be updated to include more of the newer optimizations such as Bayesian optimization.

By Hakob J

Oct 11, 2017

It is very helpful course both for theoretical and practical aspects of Hyperparameter tuning

By Juan A M C

Jan 15, 2021

Me llevo un tiempo, pero lo logre. Ahora a jugar con algunos datos y mejorar los resultados.

By manpreet s

Oct 3, 2018

good course, easy to understand and very nicely explained concepts about the neural networks

By Leonid

Oct 5, 2017

It seems the major part of this course is taken from the original "Machine Learning" course.

By Dhatri M

Jun 24, 2023

The content was taught in a way that made it easy to follow, the assignments were good too.

By Mahmoud M

Feb 10, 2022

its a great course and it delivers a lot of information in a short time and that's amazing

By Chowdepalli R R

Jul 20, 2020

tensor flow is not understood properly else the course is very good and clean to understand

By 杨之龙

Apr 4, 2018

I have to complain why dont accompany videos with quiz and notes just like the ML coursera.

By Hyatt B

Jan 9, 2018

Content great! I'm not convinced Jupyter notebooks are the best approach for this material.

By Joe S

Jan 6, 2021

A good course that provides a lot of insight into how to improve upon Deep Neural Networks

By Yen L B

Aug 31, 2018

Good explanations. But tutorials can be improved to demonstrate the various tuning effects

By Surya J

Apr 22, 2019

Great course to build intuition about tuning NN. Solid Foundation in very short duration.

By Kritika A

Mar 25, 2019

There was a lot of hand holding in programming assignments. It needs to be more rigorous.

By Vasilis S

Sep 26, 2018

Very informative course. The assignments are too trivial. Could've been more challenging.

By David D

Oct 7, 2017

Last programming assignments had some errors in them that could've easily been corrected.

By Pradeep S

Aug 6, 2023

Great course to get the basics of neural networks and deep learning as solid foundation.

By Bhargav R

May 21, 2020

Great content. Filled with rich techniques to improve models, hyperparameter tuning etc.

By Václav R

Feb 14, 2019

Could have focused a bit more on the tensorflow. Other than that - Great course, thanks!

By Rajiv C

Aug 25, 2017

It was fun to get to know other optimization techniques and how to speed up the network.

By Prajwal M H (

Apr 21, 2020

The difficulty of the course is medium. More time should be spent by learners for this