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Hyperparameter Tuning with Keras Tuner(으)로 돌아가기

Coursera Project Network의 Hyperparameter Tuning with Keras Tuner 학습자 리뷰 및 피드백

63개의 평가

강좌 소개

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....

최상위 리뷰

필터링 기준:

Hyperparameter Tuning with Keras Tuner의 7개 리뷰 중 1~7

교육 기관: Onyero W O

2022년 1월 2일

교육 기관: pranay s

2021년 9월 29일

교육 기관: Sahil V

2021년 6월 20일

교육 기관: Saharsh S

2022년 3월 28일

교육 기관: Lam C V D

2021년 1월 4일

교육 기관: Mario E S M

2022년 6월 1일

교육 기관: Rohit B

2022년 8월 3일