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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
38,091 ratings
4,051 reviews

About the Course

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

Top reviews

CV

Dec 24, 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\n\nThanks.

XG

Oct 31, 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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201 - 225 of 3,985 Reviews for Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

By hexinlin

Nov 29, 2018

great

By Nagadeepa S

Nov 13, 2018

Very easy to follow instructions. Great learning.!

By Khoo T S

Nov 14, 2018

Great course. I've learnt a lot on hyperparameter tuning and optimization strategies. The Tensorflow makes coding simpler :)

By Satyam N

Nov 13, 2018

Gives great detailed insights over parameters tuning and steps to improve the neural network performance.

By Chen N

Jan 18, 2019

Awesome as always.

By Abhishek B

Jan 16, 2019

Awesome Content and tutors!

By Raj

Jan 17, 2019

Awesome course.

By Wei L

Jan 16, 2019

Fantastic course design!

By Shravan M

Jan 17, 2019

Thank You!!!

By John l

Jan 16, 2019

good course indeed

By Kirk B

Jan 17, 2019

Andrew Ng is hands down the best teacher in this space. Excellent lectures and a well run course.

By Shayan A B

Jan 05, 2019

Another well-taught course. Cant wait to complete more in the specialization.

By Sudheer P

Jan 05, 2019

This course teaches the mechanics of deep neural networks and how to optimize the neural net. Prof goes at a reasonable pace so that the student understands the concepts.

By Qasid S

Jan 06, 2019

Great Course!! This course should be part of every deep learning career path.

By chanish a

Jan 05, 2019

I never have enjoyed this much while studying.

By Ruiliang L

Jan 06, 2019

Help you get the best understanding of the deep learning

By Babu, C

Jan 07, 2019

Excellent optimization techniques articulated very well

By Arsalan

Jan 06, 2019

I believe a approach Sir takes while teaching the course makes it comparatively easy to learn the very difficult concept of deep learning.

By Arram B

Jan 05, 2019

Thank you Andrew Ng Sir, you made every complex topic easily understandable with very efficient way.

Thanks for everything Sir!!!!

By Abdullah

Jan 07, 2019

Very thorough explanation about the hyperparameters and optimization techniques.

By Sourav

Jan 05, 2019

Learnt a great deal about tuning models. Concepts of regularization, batch norm and optimizers were very well explained.

By Sarfaraz K

Jan 19, 2019

Very well organized course by a great teacher

By Amir K

Jan 18, 2019

To the point and effective!

By Elvis S

Jan 18, 2019

Loved this part of the code... it allowed me to understand more about the optimization and regularization tricks such as RMSprop and Dropout.

By David W

Jan 19, 2019

very thoughtful introduction to various learning optimizer. easy introduction into tensorflow.

it would be better if there is more content on the local optima/saddle point issue.