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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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3201 - 3225 of 7,250 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sergio M C Z

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Jul 7, 2019

Very good course, very conceptual and well guide learning

By Stuart Z

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May 25, 2019

The final project has problems associating with itself...

By Lin Z

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May 23, 2019

Best course ever I took. Thank you, Andrew and your team.

By Ali R O

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May 22, 2019

Thank you so much I learned so many thing in this course.

By Pratik K

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Feb 5, 2019

This course is a must for every deep learning enthusiast!

By NAGARAJ R

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Jan 23, 2019

Fantastic course. Took all fear away from Deep Learning.

By Darisetty S

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Nov 20, 2018

Dhanyavadamulu! Much needed course to every AI Developer.

By Harry S

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Nov 11, 2018

very helpful, clear and concise. Everything to the point.

By Ong S L

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Oct 14, 2018

Better if we start off the entire course with tensorflow.

By Manjunath M

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Jun 24, 2018

Great Course, feels great to learn FrontLine technologies

By Cayol O

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Jun 8, 2018

Usefull trining course for a better understanding of DNN.

By Alexandre L

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Apr 28, 2018

great course, keen on learning more with the next module!

By brook a

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Apr 5, 2018

just astonishingly brilliant course by andrew ng and crew

By 陈沁然

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Mar 10, 2018

lesson is quite good, but sometimes the voice is too low.

By Pavel K

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Mar 3, 2018

As useful as the previous "Course 1". Strongly recommend!

By Abdallah M

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Jan 4, 2018

Amazing course and an amazing instructor. I learned a lot

By Shiloh T S

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Dec 3, 2017

Great dive into the art/science of hyperparameter tuning.

By Yang X

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Nov 26, 2017

Thank you Andrew! you make me love deep learning so much!

By Gultekin B (

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Nov 2, 2017

Well-prepared assignments, excellent! Thanks a lot again

By James T S

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Oct 19, 2017

Superb course that includes valuable practical knowledge.

By Chris F

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Sep 17, 2017

Everything comes together in the programming assignments!

By Sun J

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Aug 24, 2017

Very good coverage on the deeplearning technical details.

By Joseph M

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Aug 23, 2017

A brief introduction to Tensorflow is included at the end

By Umer S

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Aug 5, 2024

Great content , great community of learners and helpers!

By Srinivas C

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Jul 10, 2022

Gives clear understanding of regularization techniques.