Probability & Statistics for Machine Learning & Data Science

Overview

What you’ll learn

1. - Describe and quantify the uncertainty inherent in predictions made by machine learning models
2. - Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science
3. - Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems
4. - Assess the performance of machine learning models using interval estimates and margin of errors