Probability & Statistics for ML
Machine Learning · Beginner
Definition
Probability measures uncertainty; distributions, expectation and variance describe data.
Every ML model is built on probability.
Diagram
Flowchart
Example: Expected value of a die
faces = range(1, 7)
e = sum(faces) / 6
var = sum((f - e) ** 2 for f in faces) / 6
print(e, round(var, 3))Output: 3.5 2.917
Key points
- Normal distribution is everywhere
- Independent: P(A∩B) = P(A)P(B)
Interview questions
What is variance?
Average squared distance from the mean.