Probability - Caltech

11.07.2015 • Views

Share Embed Flag

Probability - Caltech

Probability - Caltech

DOWNLOAD ePAPER

courses.cms.caltech.edu

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

START NOW

Example: Gaussian distribu)on ! σ = Standard devia)on ! µ = mean 15

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26

Homework 2 Solutions - Caltech

CS 11 C track: lecture 1 - Caltech

Rendering, OpenGL, and Lighting - Caltech

Computer Architecture (Structure and Organization) - Caltech

Advanced Topics in Machine Learning - Caltech

approximate inference - Caltech

specifications - Caltech

Homework 1 Solutions - Caltech

CS 11 C track: lecture 2

CS 3 Introduction to Software Engineering - Caltech

CSPs - Caltech

X - Caltech

Probabilistic Graphical Models

CS 47/147 Advanced Object-Oriented Programming - Caltech

Course Overview - Caltech

Con)nuous distribu)ons ! <strong>Probability</strong> density 14

Example: Gaussian distribu)on ! σ = Standard devia)on ! µ = mean 15

Page 1 and 2: Introduc)on to Ar)ficial Intellig
Page 3 and 4: Announcements ! Grading: AvianAske
Page 5 and 6: Quan)fying Uncertainty ! So far,
Page 7 and 8: Decision making under uncertaint
Page 9 and 10: Why use probabili)es? Related ev
Page 11 and 12: Interpreta)on of probabili)es ! P
Page 13: Examples ! Bernoulli distribu)on:
Page 17 and 18: Example: Mul)variate Gaussian 17
Page 19 and 20: Marginal distribu)ons What is P(
Page 21 and 22: Condi)onal distribu)ons ! Formal
Page 23 and 24: Posterior inference ! Suppose we
Page 25 and 26: Independent RVs ! What if RVs a