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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
63,157 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

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.

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

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3301 - 3325 of 7,250 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Yang X

Jun 23, 2020

Answered many of my doubts about deep neural networks!

By Shailesh K

May 11, 2020

Simply awesome go for it. Thank you so much Andrew sir

By Varun K

May 3, 2020

Great course! Love Andrew Sir's teaching. Keep it up!!

By v. s k

Mar 31, 2020

great teaching in an easier approach. Thanks Andrew :)

By Purod D

Feb 6, 2020

I learned a lot from this course. Thank you, Coursera.

By 신우석

Jan 16, 2020

모델의 결과를 어떻게 향상시킬 수 있는지 등 세세한 부분을 잘 가르쳐주십니다. 앤드류쌤 최곱니다!

By Deleted A

Dec 30, 2019

It helped me to understand concepts of tuning in depth

By Amin N s

Jun 30, 2019

Awesome course that makes deep learning more tangible.

By Omar H E K

Jun 24, 2019

The topics were advanced and practical, I am impressed

By Jun W

May 16, 2019

Great course about tuning parameters of deep learning!

By wttc

Mar 13, 2019

very useful easy-understand and impressiving courses

By herve b

Oct 8, 2018

Très bon cours, avec en plus l'initiation à Tensorflow

By Subrato C

Sep 9, 2018

I just love it. The learning curve is perfect for me!!

By makthum s

Jul 30, 2018

One of Tough and interesting course in specialization!

By METHUKU P

Jul 6, 2018

Very good one but frameworks part is little bit clumsy

By Philipp K

Apr 30, 2018

I have learned so much of of this course. Keep it up!!

By Debasish G

Apr 7, 2018

Full of practical advice. Great course - very helpful.

By Rui X

Mar 18, 2018

The expected output is wrong in last week's assignment

By Ruslan N

Feb 6, 2018

Great course and finally an introduction to Tensorflow

By Khalid H

Oct 5, 2017

great to know such details for tuning hyperparameters!

By Allen S

Oct 4, 2017

Great information building on class one in the series.

By Bao P

Oct 1, 2023

Greate course for learning about deep neural networks

By Zixuan W

Nov 1, 2021

May be better to bring more detail about DL framework

By Spiritual S

Oct 19, 2021

Very interesting material with impactful presentation

By 林柏嘉

Sep 27, 2021

Really clear and in-depth concept about Deep Learning