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Classroom Contents
Probability for Data Science & Machine Learning
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- 1 Intro
- 2 Probability Definitions
- 3 Union
- 4 Intersection
- 5 Complement
- 6 Conditional Probability
- 7 Contingency Table
- 8 Addition Rule
- 9 Joint Probability
- 10 Dependent vs. Independent
- 11 Independent Events
- 12 Mutually Exclusive Events
- 13 Venn Diagrams
- 14 Tree Diagrams
- 15 Total Probability
- 16 Bayes' Theorem
- 17 Combinatorics
- 18 Permutations
- 19 Combinations
- 20 Poker Probabilities
- 21 Which to use?
- 22 Variations
- 23 Types of Variables
- 24 Discrete Uniform Distribution
- 25 Probability Mass
- 26 Variance
- 27 Relative Frequency Histogram
- 28 Cumulative Distribution
- 29 Expected Value
- 30 Standard Deviation
- 31 Normal Distribution
- 32 Z Score
- 33 Negative Z Score
- 34 Reverse Z Score
- 35 Confidence Intervals
- 36 Binomial Probability
- 37 Poisson Distribution
- 38 Geometric Probability
- 39 Central Limit Theorem
- 40 Negative Binomial Probability
- 41 Which to use?
- 42 Negative Binomial Formula
- 43 Hypergeometric Distribution
- 44 Continuous Probability
- 45 Continuous Probability Formula
- 46 Exponential Distribution
- 47 Exponential Formulas
