Bayesian Machine Learning for Optimization in Python

Learn Bayesian optimization and statistical modeling to tackle high-dimensional problems. Explore hyperparameter tuning, experimental design, algorithm configuration, and system optimization.

5.0

32 Lessons

Updated 4 weeks ago

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Bayesian optimization allows developers to leverage Bayesian inference and statistical modeling to efficiently search for the optimal solution in a high-dimensional space. Starting with the fundamentals of statistics and Bayesian statistics, you’ll explore different concepts of machine learning and its applications in software engineering. Next, you’ll discover different strategies for optimizations. Through practical examples and hands-on exercises, you’ll gain proficiency in implementing Bayesian optimization algorithms and fine-tuning them for specific tasks. By the end of the course, you’ll have a comprehensive understanding of the entire Bayesian optimization workflow, from problem formulation to solution optimization. By completing this course, you’ll be able to tackle complex optimization problems more efficiently and effectively. You’ll be equipped to find optimal solutions in areas such as hyperparameter tuning, experimental design, algorithm configuration, and system optimization.

Bayesian optimization allows developers to leverage Bayesian inference and statistical modeling to efficiently search for the op...Show More

WHAT YOU'LL LEARN

An understanding of Bayes’ theorem and its applications

Familiarity with the core components of Bayesian machine learning and its application to optimization

Hands-on experience tuning hyperparameters using Bayesian optimization

The ability to attain optimized solutions for complex problems using Bayesian statistics

Familiarity with core components of the Dragonfly framework for scalable Bayesian optimization

An understanding of Bayes’ theorem and its applications

TAKEAWAY SKILLS

Python

Python 3

Python Programming

Data Science

Machine Learning

Machine learning paradigms

Optimization

Neural Networks

Deep neural networks

Deep Learning

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Course Author:

Danial Amin

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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