Your SlideShare is downloading. ×
0
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Probability And Stats Intro
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Probability And Stats Intro

590

Published on

Published in: Technology, Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
590
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
28
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  1. Crash course in probability theory and statistics – part 1 Machine Learning, Mon Apr 14, 2008
  2. Motivation Problem: To avoid relying on “magic” we need mathematics. For machine learning we need to quantify: ●Uncertainty in data measures and conclusions ●“Goodness” of model (when confronted with data) ●Expected error and expected success rates ●...and many similar quantities...
  3. Motivation Problem: To avoid relying on “magic” we need mathematics. For machine learning we need to quantify: ●Uncertainty in data measures and conclusions ●“Goodness” of model (when confronted with data) ●Expected error and expected success rates ●...and many similar quantities... Probability theory: Mathematical modeling when uncertainty or randomness is present. P  X = x i , Y = y j = pij

×