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
63,291 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 ne...
...

Top reviews

DD

Mar 28, 2020

I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

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

Filter by:

7176 - 7200 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Tanurima M

•

Jul 4, 2020

The course is outstanding just the tensorflow library should be taught more in details.

By Pranjal S

•

May 15, 2020

The technologies and the assignments should be updated to follow the latest standards

By Chaobin Y

•

Nov 3, 2017

Maybe this course can merge with the 1st one. they both cover too little materials.

By ognjen m

•

Nov 17, 2022

last week is rushed and not greatly explained. Especially in the work assigment

By P A A H

•

Sep 12, 2020

WEEK-3 was a little bit messy, it would have been better if it was tensorflow 2

By joel a

•

Apr 25, 2020

taught concepts well, but the programming assignments felt like it was spoonfed

By Xieming L

•

May 12, 2018

Good: Contents on Tensor Flow

Bad: No real useful content compared the Course 1.

By Péter D

•

Oct 6, 2017

great lectures, simplistic programming assignements, ridiculously easy tests

By SAMBATH S

•

Aug 2, 2020

It would be better to use TF2 as there are lots of changes in the usages.

By Di W

•

Jan 18, 2018

Harder to understand. Overall quality is not as good as the first class.

By Kenneth Z

•

Mar 20, 2018

It is a bit abrupt to jump into tensorflow without explaining in depth.

By Rishab K

•

Apr 17, 2020

good course to learn, but more assignments should be introduce n week3

By Rajat K S

•

Jan 11, 2020

Most of the solutions to the assignment were written in instructions.

By Ganesan G

•

Dec 28, 2017

I am not getting to see the programming exercises that i have done :(

By Adam S

•

Oct 24, 2022

Some good stuff, but very slow, and the coding was pretty trivial.

By Jonghyun K

•

Apr 25, 2020

voice was too small compared to noises made by clothes and others.

By Aastha S

•

Jul 14, 2021

More explanations required for functions used in tensorflow lab

By FREDERIC T

•

May 13, 2018

Good courses, the sound quality is very poor (high tone noise).

By Suhas M

•

Jan 20, 2019

Interface for evaluating is not great and assignments are easy

By Alex

•

Sep 4, 2017

The Tensorflow part should have started sooner in the course.

By Aloys N

•

Jul 1, 2019

We could have more guidance on setting a tensorflow model

By HAMM,CHRISTOPHER A

•

Apr 30, 2018

Lots of theory and not enough practical implementation.

By Stefan S

•

Sep 22, 2020

Content starts to feel old, but still interesting.

By Tadeu V (

•

Jan 30, 2025

I was expecting a more hands-on practical course.

By Hasnaa T

•

Feb 10, 2020

the circulum was some hard and over detailed