Linear Regression

Linear regression is a vital machine learning tool that is widely used in predictive modeling. This course offers an in-depth understanding of the principles and practice of linear regression, covering topics such as cost function, R squared metric, hypothesis testing, and computational implementation. To fully grasp the details, basic mathematics is necessary, including a basic understanding of linear algebra and differential calculus. The course also explores important machine learning concepts like cost function, F test, and cross-validation. Additionally, it delves into hypothesis testing and the commonly used term "P value". The SherlockML data science platform is used to teach linear regression, and learners get free access to the platform. The course aims to equip learners with the skills necessary to become machine learning job seekers where demand exceeds supply. The data scientists behind ASI Data Science are Angie Ma, Gary Willis, and Alessandra Sttagliano, who have over 2,500 members in their community of data scientists and engineers. Together, they have collaborated on more than 150 commercial AI/machine-learning projects.