@@ -16,3 +16,40 @@ In this talk, I will discuss how you can use your coding skills to "hack probabi
1616> "Not once, but twice AI was revolutionized by people who understood Probability Theory"<br >
1717
1818-Stanford University | CS 109: Probability for Computer Scientists
19+ 20+ #### Talk Structure
21+ 22+ 1 . Introduction<br >
23+ a. About me<br >
24+ b. Questions to know audience<br >
25+ c. Motivation
26+ 27+ 2 . Talk's Target
28+ 3 . Diving into Probability (interactive way)<br >
29+ a. Coin toss experiment using JQuery<br >
30+ b. Comparing theoretical Vs experimental probability with D3js<br >
31+ c. Simulating coin-toss experiment with Python<br >
32+ 33+ 4 . Ingredients to Modelling Uncertainty<br >
34+ a. Sample space<br >
35+ b. Axioms of Probability<br >
36+ 37+ 5 . Introduction to Random Variables
38+ 39+ 6 . Relation between Random Variables<br >
40+ a. Joint Probability<br >
41+ b. Marginal Probability<br >
42+ c. Conditional Probability<br >
43+ d. Dependence & Independence
44+ 45+ 7 . Demystifying Bayes' Theorem
46+ 47+ 8 . Application of Probability Theory<br >
48+ a. Naive Bayes Algorithm for Spam filtering<br >
49+ 50+ 9 . Take Away message
51+ 52+ 10 . Thank you
53+ 54+ 11 . References
55+
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