Bayesian Optimization with Python
Offered By: Coursera Project Network via Coursera
Course Description
Overview
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.
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.
Taught by
Farhad Abdi
Related Courses
Design Computing: 3D Modeling in Rhinoceros with Python/RhinoscriptUniversity of Michigan via Coursera A Practical Introduction to Test-Driven Development
LearnQuest via Coursera FinTech for Finance and Business Leaders
ACCA via edX Access Bioinformatics Databases with Biopython
Coursera Project Network via Coursera Accounting Data Analytics
University of Illinois at Urbana-Champaign via Coursera