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

4.9
stars
63,156 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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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5651 - 5675 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By P S P R

Dec 2, 2017

very good

By 姚朴健

Nov 27, 2017

very good

By SAKURA

Nov 19, 2017

吴恩达男神男神男神

By hugo

Nov 9, 2017

wonderful

By Andrés R d V

Oct 31, 2017

Very good

By chun

Oct 25, 2017

very good

By Michel-Alexandre C

Oct 24, 2017

Excellent

By 陈尚伟

Oct 9, 2017

Ng出品,必属精品

By 超 宋

Oct 8, 2017

very nice

By password

Oct 5, 2017

very good

By Sylvain D

Oct 5, 2017

Excellent

By Denny M

Sep 24, 2017

Nice! :-)

By LI S

Sep 19, 2017

very good

By 霍宇琦

Sep 18, 2017

thank you

By Hugsy W

Sep 17, 2017

very good

By Santosh P

Sep 17, 2017

Wonderful

By Yanqing Y

Sep 13, 2017

very good

By Arturas N

Sep 8, 2017

Good info

By hanpaopao

Sep 7, 2017

very good

By chang c

Sep 5, 2017

very good

By laixiaohang

Sep 3, 2017

very good

By WXB506

Aug 24, 2017

内容比较基础,不错

By Naman B

Aug 23, 2017

Amazing !

By kai w

Aug 22, 2017

very good

By Seyyed M M

Jun 17, 2023

Awesome!