返回到 Avoid Overfitting Using Regularization in TensorFlow
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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
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