Probability & Statistics for Machine Learning & Data Science
Completed by Nick Peterson
November 10, 2024
33 hours (approximately)
Nick Peterson's account is verified. Coursera certifies their successful completion of Probability & Statistics for Machine Learning & Data Science
What you will learn
Describe and quantify the uncertainty inherent in predictions made by machine learning models
Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science
Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems
Assess the performance of machine learning models using interval estimates and margin of errors
Skills you will gain
- Category: Bayesian Statistics
- Category: Probability
- Category: Statistical Analysis
- Category: Probability Distribution
- Category: Statistical Methods
- Category: Statistical Machine Learning
- Category: Statistical Hypothesis Testing
- Category: Correlation Analysis
- Category: A/B Testing
- Category: Statistical Inference
- Category: Sampling (Statistics)
- Category: Descriptive Statistics
