Probability for Data Science & Machine Learning

Probability for Data Science & Machine Learning

Derek Banas via YouTube Direct link

Addition Rule

8 of 47

8 of 47

Addition Rule

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Classroom Contents

Probability for Data Science & Machine Learning

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

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