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學生對 Coursera Project Network 提供的 Avoid Overfitting Using Regularization in TensorFlow 的評價和反饋

4.8
74 個評分
4 條評論

課程概述

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 個評論(共 4 個)

創建者 Ishwari R

2020年8月7日

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

創建者 tale p

2020年6月26日

good

創建者 Ricardo D

2021年1月30日

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

創建者 Deleted A

2020年5月12日

Not efficiently