Probability and Bayes Theorem
Joint/conditional probability, independence, Bayes theorem with real AI examples.
Probability Basics
A probability is a number from 0 to 1 measuring how likely an event is. Conditional probability P(A|B) is the chance of A given that B happened.
Conditional Probability
P(A|B) = P(A and B) / P(B). Conditioning narrows the sample space to the cases where B is true.
p_a_and_b = 0.12
p_b = 0.30
print(p_a_and_b / p_b) # P(A | B) = 0.4All lessons in this course
- Descriptive Statistics and Distributions
- Probability and Bayes Theorem
- Hypothesis Testing
- Correlation and Covariance