Bayesian Optimization with Python

3.7
7 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

Define objective function of Bayesian optimization

Implement Bayesian Optimization

Use Bayesian Optimization and GPyOpt in your projects

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this guided project you will get familiar with the basics of Bayesian optimization and Implement Bayesian optimization algorithm process and use it in a machine learning project, We will consider function optimization task and also Hyperparameters tuning using Bayesian optimization and GPyOpt library. Bayesian optimization is a nice topic, whether you want to do a high dimensional or a computationally expensive optimization it's efficient. By the end of this project you will be able to understand and start applying Bayesian optimization in your machine learning projects.

您要培養的技能

Bayesian OptimizationPython ProgrammingMachine LearningGpyOpt

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Define Objective function - One Dimensional Case

  2. Optimize 1-D Objective function using GPyopt

  3. Define Objective function - Two Dimensional Case

  4. Optimize 2-D Objective function using GPyopt

  5. Using Bayesian Optimization in Machine Learning

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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