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
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent