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

4.9
stars
63,238 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.

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.

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2976 - 3000 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Narayanan S

Mar 19, 2019

Very practical content. Good introduction to frameworks as well.

By Tushar K

Feb 2, 2019

This course helped me a lot in understanding the hyperparameters

By Sijie

Jan 10, 2019

get a lot of insight about how to improve my own neural network.

By ahmadreza a

Nov 27, 2018

please correct the mistake in the week 3 assignment, placeholder

By Nicolò R

Sep 26, 2018

Wonderful course, it has both theory and implementation details.

By Stuart C

Sep 14, 2018

great course which helps with more in-depth neural network ideas

By Krzysztof O

Sep 2, 2018

Thank you Andrew for this magnificent course and specialization.

By Mohamed C S

Jul 16, 2018

Excellent course, very clear videos and programming assignments!

By Shobhit G

Jun 27, 2018

well taught course. The way its taught makes the concepts stick.

By Ed H

Jun 10, 2018

Very good courses for the learning of DNN optimization problems.

By XIAO N (

Apr 25, 2018

Very practical advice on how to fine tuning your neural networks

By Rodolfo C

Mar 21, 2018

Great introduction to hyperparameters adjustment and Tensor flow

By Chertushkin M

Mar 17, 2018

Fantastic course. Thank you, Andrew NG and deeplearning.ai team!

By S N

Feb 12, 2018

Great Course with good fundamentals.More exercises would be nice

By Rafael L

Feb 2, 2018

A bit less interesting than first one, but still a great course.

By Junheng Z

Jan 14, 2018

It is really great and it help you to get starting to Tensorflow

By Daniel S

Nov 7, 2017

Great tips for tuning networks and finally know what softmax is!

By Zwiebel

Nov 6, 2017

Introduction of Tensorflow is concise and to the point as usual!

By zeeshan s

Oct 28, 2017

Great intro to tensorflow after learning the underlying concepts

By Farrukh

Oct 18, 2017

Complicated ideas presented very clearly! Would highly recommend

By 王贤

Oct 3, 2017

Ng的课一如既往的浅显易懂,而且十分有用,希望能学习更多有关tensorflow方面的内容,不知道后面几门课是否会经常使用该框架

By aisling.he

Sep 23, 2017

it helps a lot for me to understand the Neuarl networks! thanks!

By Yi W

Sep 12, 2017

Very practical tips and intuitive explanations for these tricks.

By Keith B

Sep 6, 2017

hurray! more good stuff, and nice intro to tensorflow in week 3

By 臧雷

Sep 5, 2017

Practical knowledge about how to implement a NN that works well.