How do neurons give rise to probabilistic programming
13
Why are we using web ppl
14
Storing Variables
15
Storing Attributes
16
Redefine Attributes
17
Else Statement
18
QuestionMark Operator
19
Functions
20
Differences from JavaScript
21
Practice Problems
22
Concepts
23
Flip Away
24
Memoization
25
Recursion
26
Bonus
27
Questions
Description:
Explore probabilistic programming in this 1-hour 10-minute tutorial by Kevin Smith from MIT, presented at the BMM Summer Course 2018. Dive into key concepts such as computational theory of mind, intuitive physics engine, and probabilistic inference. Learn about the structure of probabilistic languages, storing variables and attributes, and using functions. Practice with hands-on problems covering concepts like flip away, memoization, and recursion. Gain insights into how neurons contribute to probabilistic programming and understand the advantages of using web-based probabilistic programming languages.