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学生对 DeepLearning.AI 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的评价和反馈

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课程概述

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....

热门审阅

BA

May 31, 2020

Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!I will pass on what I have learned here to undergrads :)

DH

Apr 26, 2020

Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.

筛选依据：

2976 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3000 个评论（共 7,286 个）

创建者 Roland G

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Oct 3, 2019

As in part 1, good pace, excellent and comprehensive assignments

创建者 Shashank Y

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Aug 26, 2019

great course, refreshed the knowkedge, thanks to andrew and team

创建者 Faline F

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Aug 24, 2019

The explanation of intuition behind each algorithm is very good.

创建者 Hossein E Z

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Jul 19, 2019

This course was so useful to my knowledge on improving networks.

创建者 Raja s v

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Jun 19, 2019

Great insight, practical approach. Really helpful course Thanks.

创建者 YC X

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Jun 9, 2019

Easy to understand. The professor is very professional and nice.

创建者 Veera V S S P

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May 12, 2019

A simple explanation of the basic concepts. Thank you Andrew Ng.

创建者 Maciej F

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Apr 26, 2019

5 stars for the horse picture in the saddle point explanation :D

创建者 Narayanan S

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Mar 18, 2019

Very practical content. Good introduction to frameworks as well.

创建者 Tushar K

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Feb 2, 2019

This course helped me a lot in understanding the hyperparameters

创建者 Sijie

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Jan 9, 2019

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

创建者 Nicolò R

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Sep 26, 2018

Wonderful course, it has both theory and implementation details.

创建者 Stuart C

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Sep 14, 2018

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

创建者 Krzysztof O

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Sep 2, 2018

Thank you Andrew for this magnificent course and specialization.

创建者 Mohamed C S

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Jul 16, 2018

Excellent course, very clear videos and programming assignments!

创建者 Shobhit G

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Jun 27, 2018

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

创建者 Ed H

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Jun 10, 2018

Very good courses for the learning of DNN optimization problems.

创建者 XIAO N (

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Apr 25, 2018

Very practical advice on how to fine tuning your neural networks

创建者 Rodolfo C

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Mar 21, 2018

Great introduction to hyperparameters adjustment and Tensor flow

创建者 Chertushkin M

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Mar 17, 2018

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

创建者 S N

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Feb 12, 2018

Great Course with good fundamentals.More exercises would be nice

创建者 Rafael L

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Feb 2, 2018

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

创建者 Junheng Z

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Jan 13, 2018

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

创建者 Daniel S

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Nov 6, 2017

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