Voltar para Hyperparameter Tuning with Keras Tuner
Comentários e feedback de alunos de Hyperparameter Tuning with Keras Tuner da instituição Coursera Project Network
36 classificações
Sobre o curso
In this 2-hour long guided project, we will use Keras Tuner to find optimal hyperparamters for a Keras model. Keras Tuner is an open source package for Keras which can help machine learning practitioners automate Hyperparameter tuning tasks for their Keras models. The concepts learned in this project will apply across a variety of model architectures and problem scenarios. Please note that we are going to learn to use Keras Tuner for hyperparameter tuning, and are not going to implement the tuning algorithms ourselves. At the time of recording this project, Keras Tuner has a few tuning algorithms including Random Search, Bayesian Optimization and HyperBand.
In order to complete this project successfully, you will need prior programming experience in Python. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, and optimization algorithms like gradient descent but want to understand how to use Keras Tuner to start optimizing hyperparameters for training their Keras models. You should also be familiar with the Keras API.
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.
Filtrar por:
1 — 3 de 3 Avaliações para o Hyperparameter Tuning with Keras Tuner
por pranay s
•29 de Set de 2021
loved it hope to find new courses like this
por Sahil V
•20 de Jun de 2021
Helpful foundation course for Keras Tuner.
por Lam C V D
•4 de Jan de 2021
Too complicated
Coursera Footer
© 2021 Coursera Inc. Todos os direitos reservados.
