INTRODUCTION TO DATA SCIENCE
WFAiS UJ, Informatyka Stosowana II stopień studiów
1
5/12/2017
This lecture is
based on course by E. Fox and C. Guestrin, Univ of Washington
What we’ve learned so far
5/12/2017
2
Nearest neighbor search
Nearest neighbor search
5/12/2017
3
Nearest neighbor search
5/12/2017
4
Nearest neighbor search
5/12/2017
5
Nearest neighbor search
5/12/2017
6
Nearest neighbor search
5/12/2017
7
Nearest neighbor search
5/12/2017
8
Nearest neighbor search
5/12/2017
9
Nearest neighbor search
5/12/2017
10
Nearest neighbor search
5/12/2017
11
Nearest neighbor search
5/12/2017
12
Nearest neighbor search
5/12/2017
13
Nearest neighbor search
5/12/2017
14
Nearest neighbor search
5/12/2017
15
Nearest neighbor search
5/12/2017
16
What we’ve learned so far
5/12/2017
17
k-means and MapReduce
k-means and MapReduce
5/12/2017
18
k-means and MapReduce
5/12/2017
19
k-means and MapReduce
5/12/2017
20
k-means and MapReduce
5/12/2017
21
k-means and MapReduce
5/12/2017
22
k-means and MapReduce
5/12/2017
23
k-means and MapReduce
5/12/2017
24
What we’ve learned so far
5/12/2017
25
Mixture models
Mixture models
5/12/2017
26
Mixture models
5/12/2017
27
Mixture models
5/12/2017
28
Mixture models
5/12/2017
29
Mixture models
5/12/2017
30
Mixture models
5/12/2017
31
Mixture models
5/12/2017
32
Mixture models
5/12/2017
33
Mixture models
5/12/2017
34
Mixture models
5/12/2017
35
Mixture models
5/12/2017
36
What we’ve learned so far
5/12/2017
37
Latent Dirichlet allocation
Latent Dirichlet allocation
5/12/2017
38
Latent Dirichlet allocation
5/12/2017
39
Latent Dirichlet allocation
5/12/2017
40
Latent Dirichlet allocation
5/12/2017
41
Latent Dirichlet allocation
5/12/2017
42
Latent Dirichlet allocation
5/12/2017
43
Latent Dirichlet allocation
5/12/2017
44
Latent Dirichlet allocation
5/12/2017
45
Latent Dirichlet allocation
5/12/2017
46
Summary of what we have learned
5/12/2017
47
