Chevron Left
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
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

Filter by:

2326 - 2350 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By honglianglv

•

Sep 16, 2018

very good course! It help me to know how to speed up training and tune hyperparameters

By Dan L

•

Aug 3, 2018

Practical advice! One needs to dig into the project to find how useful this course is.

By Celine H

•

Jun 7, 2018

Very good overview for nn optimization and hyperparameter tuning! Easy to follow along

By Lidor A

•

May 2, 2018

Priceless advises and techniques! May thanks for Andrew and the rest of the TA team!!!

By Carlos H B

•

Apr 21, 2018

If you want understand the nuts associated with NN and Deep Learning.. this is for you

By Salim L

•

Mar 16, 2018

The best consolidation to date of best practices to improve your Deep Learning models.

By aditya g

•

Feb 16, 2018

Very nice explanation of applied deep learning concepts. Great work Andrew & Team...!!

By Tamilarasu S

•

Jan 21, 2018

This course gives some of the important techniques to increase performance of a model.

By Dhaval D

•

Nov 8, 2017

Amazing course and introduction to concepts specific to deep learning. Really like it.

By Markus L

•

Oct 26, 2017

Excellent course, dives deep enough to get the insight whats happening with each knob.

By clement G

•

Oct 6, 2017

Awesome, the GD optimization techniques and introduction to TF were imo the best part.

By Evaldas B

•

Sep 27, 2017

Very good course to go depper in understanding deepm learning improovement techniques.

By Arnab S

•

Sep 8, 2017

Very well designed course. Now I feel confident about various optimization algorithms.

By Wu P

•

Aug 31, 2017

Very informative, I have finally understand ADAM, RMSprop after this course, thanks !!

By ZHEN Z

•

Aug 29, 2017

The course is illuminating , but the assignment is too easy to consolidate knowledge.

By Esa A

•

Feb 6, 2024

Very nice course. Upgrading the Tensorflow version might be helpful if not necessary.

By Rene A D P

•

Jan 1, 2023

really good, although the last programming lab does gives issues to a lot of learners

By aniket y

•

Jul 28, 2022

Very good containt of the course and it excellenct part is its quizes or assignments.

By Ayush P

•

Feb 12, 2022

Its am excellent course to learn basics of machine learning and deep learning models

By Mohamed S

•

Dec 31, 2020

I would like to take the opportubity to thank Deeplearning.AI team for the great work

By Sujan R

•

Oct 26, 2020

Very good course and as always, Andrew Ng does very good job and explaining concepts.

By Zhongtian Y

•

Aug 24, 2020

I think I got used to Andrew's Class and it become much understandable once you adapt

By Jatin G

•

Jul 9, 2020

The comments in jupyter notebook are very well written to explain the code and tasks.

By Varsha G

•

Jul 6, 2020

It would be better to have more assignments where we have to do everything on our own