Linear regression is a commonly used technique, and parts of it are often justified by heuristics. In this video, we discuss the assumptions behind linear regression, and we show how it can be derived from statistical principles. We focus on the use of mean squared error as the error metric and regularization terms, showing how they are both derived from assumptions about the nature of noise in our data.

We offer practical and actionable training that provides immediate impact to candidates by focusing on what works. Based on decades of hands-on experience, our immersive programs set the benchmark for professional data education.

Our alumni are the pillar of our brand—they’ve trusted our programs and elevated their skills with top-tier career training to get hired with stand-out partners. Our alumni have exclusive access to our network of hiring partners, including thousands of companies around the world, from startups to Fortune 500, who apply our models to drive their business and power their data teams.

We don’t just do training—we provide proven methodologies, adaptable resources, experienced instructors, a robust hiring program and world-class support.

Watch the On-Demand Video

Download the eBook

"*" indicates required fields

Name*