Retour à Avoid Overfitting Using Regularization in TensorFlow
Avis et commentaires pour d'étudiants pour Avoid Overfitting Using Regularization in TensorFlow par Coursera Project Network
74 évaluations
À propos du cours
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.
Meilleurs avis
Filtrer par :
1 - 4 sur 4 Avis pour Avoid Overfitting Using Regularization in TensorFlow
par Ishwari R
•7 août 2020
please enable me to reset the deadlines as i was unable to complete..
par tale p
•26 juin 2020
good
par Ricardo D
•30 janv. 2021
Good introduction to regularization techniques. It's nice to learn these techniques with a relevant, but simple, example code.
par Deleted A
•12 mai 2020
Not efficiently
Coursera Footer
© 2022 Coursera Inc. Tous droits réservés.
