Probability & Statistics for Machine Learning & Data Science

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