In this Introductory course on Statistics and Probability, you will learn the mathematical concepts required for Machine Learning. You will first start with the basics of probability followed by different methods for the use of probability in Machine Learning Study. These will be explained with case studies and examples. You will next learn about the rules of basic probability calculation. This will be followed up with learning Bayes Theorem. To conclude you will understand distributions and explore normal distribution in depth.
Skills covered
Probability Theory
Introduction to probability
Rules for probability calculation
Bayes Theorem
Normal Distribution
Course Syllabus
Statistical Learning
Case study on statistics and probability theory
Solution for case study
Introduction to probability
Rules for probability calculation
Bayes theorem Normal distribution