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Volver a Avoid Overfitting Using Regularization in TensorFlow

Opiniones y comentarios de aprendices correspondientes a Avoid Overfitting Using Regularization in TensorFlow por parte de Coursera Project Network

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4 reseña

Acerca del Curso

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 - 4 de 4 revisiones para Avoid Overfitting Using Regularization in TensorFlow

por Ishwari R

7 de ago. de 2020

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

por tale p

26 de jun. de 2020

good

por Ricardo D

30 de ene. de 2021

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

por Deleted A

12 de may. de 2020

Not efficiently