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学生对 Coursera Project Network 提供的 Avoid Overfitting Using Regularization in TensorFlow 的评价和反馈

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74 个评分
4 条评论

课程概述

In this 2-hour long project-based course, you will learn the basics of using weight regularization and dropout regularization to reduce over-fitting in an image classification problem. By the end of this project, you will have created, trained, and evaluated a Neural Network model that, after the training and regularization, will predict image classes of input examples with similar accuracy for both training and validation sets. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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1 - Avoid Overfitting Using Regularization in TensorFlow 的 4 个评论(共 4 个)

创建者 Ishwari R

Aug 7, 2020

please enable me to reset the deadlines as i was unable to complete..

创建者 tale p

Jun 26, 2020

good

创建者 Ricardo D

Jan 30, 2021

Good introduction to regularization techniques. It's nice to learn these techniques with a relevant, but simple, example code.

创建者 Deleted A

May 12, 2020

Not efficiently