Bootstrapping the Right Way - Data Science Best Practices
Offered By: GOTO Conferences via YouTube
Course Description
Overview
Learn how to properly implement bootstrapping techniques in data science and machine learning applications. Explore key takeaways from Yanir Seroussi's talk at YOW! 2019, including avoiding single-sample confidence interval comparisons, using sufficient resamples, leveraging robust bootstrapping packages, selecting appropriate bootstrap methods, considering parametric Bayesian approaches, and implementing thorough testing practices. Gain insights into advanced statistical techniques for improving the reliability and accuracy of your data analysis and machine learning models.
Syllabus
Bootstrapping the Right Way • Yanir Seroussi • YOW! 2019
Taught by
GOTO Conferences
Related Courses
Introduction to Probability, Statistics, and Random ProcessesUniversity of Massachusetts Amherst via Independent Bayesian Statistics
Duke University via Coursera Bayesian Statistics: From Concept to Data Analysis
University of California, Santa Cruz via Coursera Improving your statistical inferences
Eindhoven University of Technology via Coursera Bayesian Statistics: Techniques and Models
University of California, Santa Cruz via Coursera