Avoid Overfitting Using Regularization in TensorFlow に戻る
Coursera Project Network による Avoid Overfitting Using Regularization in TensorFlow の受講者のレビューおよびフィードバック
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コースについて
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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Avoid Overfitting Using Regularization in TensorFlow： 1 - 4 / 4 レビュー
by Ishwari R
•2020年8月7日
please enable me to reset the deadlines as i was unable to complete..
by tale p
•2020年6月26日
good
by 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.
by Deleted A
•2020年5月12日
Not efficiently
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