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

4.9
stars
63,221 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

JS

Apr 4, 2021

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

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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6751 - 6775 of 7,257 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Shivanshu K S

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Apr 5, 2022

Great course. The tensor flow introduction part could have been better.

By Delowar S

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Jun 2, 2020

this course will help me to improve my academic skill beside help future

By Shahin A

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Apr 18, 2020

i rate this course 4, its really good one and learned alot in the course

By ATIK M

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Apr 25, 2019

Good can be improved by providing more code based video like Tensorflow.

By Benjamin M

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Jul 24, 2020

More explanation for some of the tensorflow code could have been given.

By Olena I

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Apr 23, 2020

I think TensorFlow is outdated, PyTorch is the way to go in the future.

By Jaap d V

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Jan 7, 2020

Some tricky parts in the programming assignments. otherwise great class

By alfredo g

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May 29, 2019

too math, i hope futher parts contain more implementation than calculus

By Imran P

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Oct 4, 2017

I'd like a little more focus on tensorflow, perhaps starting at week 1.

By Babu L P M

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Oct 19, 2023

If can be better if more details on introduction to tensorflow added

By Prateek L

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Mar 27, 2020

There should be more examples first of all then moving to mathematics.

By Mohammad A

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Feb 25, 2020

Great Explation of hyperparameter tuning and best intro to Tensorflow.

By Pascal A S

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Jul 22, 2019

A bit too technical for my taste. But useful examples to work through.

By Rindra R

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Oct 10, 2017

Good curriculum and to the point. TensorFlow introduced a little late.

By Yousif A

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May 24, 2021

My one critique is that the TensorFlow topic was suddenly introduced.

By Ashish G

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Apr 27, 2020

course is not updates to tensorflow 2 but overall it is very helpful.

By Fabio S

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Nov 3, 2019

Suggestion of references, as a complement, would be very interesting.

By Marcos C

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Nov 3, 2019

Content needs update to leverage the state of the art in the subject.

By Cristhian B

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Aug 27, 2019

It's a hard course but the materials are great and their explanations

By Srivatsan R

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Jun 29, 2018

Needs more real coding exercises taht aren't mainly just copy & paste

By jian29ye4

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Oct 23, 2017

generally good but hope to get more assignment about parameter tuning

By Kalp K V

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May 21, 2020

Course was insightful but seemed difficult to grasp at some moments.

By Vishal C

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Mar 28, 2019

Tough Concepts are not explained clearly like dropout regularization

By Silvério M P

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Aug 31, 2018

Not as much detail on the topics as the first specialization course.

By Mahendren T

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Oct 30, 2017

Learnt a lot, assignments not as complex as would have hoped though.