King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Search
August 31, 2015
KAUST
An Example Problem
Four Components for a Problem
Initial state of the problem
A description of the possible actions available
to the agent. Successor function determines
all states reachable from the ini
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Data
October 26, 2015
KAUST
Questions to Answer
What is data?
What kinds of attributes can be used to
describe objects?
How data are different in types?
How can we improve data quality?
How to measure similarities between
objects?
2
W
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Adversarial Search
October 12, 2015
KAUST
Recall from Last Lectures
Weve seen a lot of search strategies
Uninformed search: breadthfirst search, uniformcost
search, depthfirst search, iterative deepening search,
bidirectional sea
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Decision Trees
December 2, 2015
KAUST
Decision Trees
Decision trees are methods for inductive learning
The method takes a set of attributes (in this case
questions) as inputs and outputs a decision (in
this case a person), and build
King Abdullah University of Science and Technology
Data Structure
CS 160

Fall 2014
CS 160 Data Structures and Algorithms
Fall 2014: Assignment 2
Instructions:
1. The total points of this assignment are 100. The points of each exercise appear on the
corresponding title.
2. Submission deadline is 29/10/2014 at 12 midnight.
3. For the prog
King Abdullah University of Science and Technology
Data Structure
CS 160

Fall 2014
Name: _
ID:_
CS 160 Data Structures and Algorithms
Fall 2014: Midterm exam
Exercise 1: (10+5+10 = 25pts)
The following is the insertion sort algorithm studied in class:
INSERTIONSORT(A)
for j = 2 to A.length
key = A[j]
/ Insert A[j] into the sorted seque
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Introduction to Data Mining
October 26, 2015
KAUST
What is Data Mining?
Data mining is the process of discovering
unknown/new patterns from large data sets
involving methods from statistics and
artificial intelligence but also databas
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Nave Bayes
November 16, 2015
KAUST
An Example
Lets learn classifiers by learning P(YX)
Y = grades, X = <attend lectures, work hard>
Attend
Lectures
Work Hard
P(AAL, WH)
P(BAL, WH)
Y
Y
0.86
0.14
Y
N
0.72
0.28
N
Y
0.58
0.42
N
N
0.1
King Abdullah University of Science and Technology
Data Structure
CS 160

Fall 2014
CS 160 Data Structures and Algorithms
Fall 2014: Assignment 1
Instructions:
1. The total points of this assignment are 100. The points of each exercise appear on the
corresponding title.
2. Submission deadline is 14/10/2014 at 12 midnight.
3. For the prog
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Data Exploration
November 2, 2015
KAUST
Techniques in Data Exploration
Summary statistics
Visualization
2
Summary Statistics
Summary statistics are numbers that summarize
properties of the data
Summarized properties include frequency,
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Logistic Regression
November 30, 2015
KAUST
Logistic Regression
Motivation: we have learned naive Bayes
which computes P(YX) by learning P(Y) and
P(XY), why dont we learn P(YX) directly?
Logistic Regression
Consider learning f: X
King Abdullah University of Science and Technology
Data Structure
CS 160

Fall 2014
CS 160 Data Structures and Algorithms
Fall 2014: Assignment 3
Instructions:
1. The total points of this assignment are 100. The points of each exercise appear on the
corresponding title.
2. Submission deadline is 2/12/2014 at 12 midnight.
3. For the progr
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
1. Introduction (Search and Sorting)
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 88
Preface
This course is devoted to
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
6. Randomized Algorithms
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 57
Randomized Algorithms
We will consider exampl
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
5. Greedy Algorithms
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 54
Greedy Algorithms
Greedy algorithms are algorithm
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
4. Dynamic Programming
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 47
Dynamic Programming
The idea of dynamic program
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
8. Work with NPHard Problems
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 33
Work with NPHard Problems
In this secti
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
10. Computations and Unsolvable Problems
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 37
Model of Computation
To understand more deepl
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
9. Partial Recursive Functions
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 31
Partial Recursive Functions
In this sec
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
CS 260
Design and Analysis of Algorithms
7. P and NP
Mikhail Moshkov
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology
1 / 29
P and NP
In this section, we will study the classes P and
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
Homework 2
Fall 2015: CS 260 Design and Analysis of Algorithms
Instructions: This homework is due on Sunday, October 4, 2015 in class. You should work individually (not in groups) and submit it handwritten on A4size papers. Write your name clearly on top
King Abdullah University of Science and Technology
algorithm
CS 260

Fall 2016
Homework 1
Fall 2015: CS 260: Design and Analysis of Algorithms
Instructions: This homework is due on Wednesday, September 9, 2015 in class. You should work
individually (not in groups) and submit it handwritten on A4size papers. Write your name clearly
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Local Search &
Constraint Satisfaction Problems
September 7, 2016
KAUST
From Last Lecture
A* is the most widelyknown form of bestfirst
search
Evaluation function: = + (),
is the cost to reach the node, and () is
the cost to get f
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220 Data Analytics
Logistic Regression
November 21, 2016
KAUST
Logistic Regression
Motivation: we have learned naive Bayes
which computes P(YX) by learning P(Y) and
P(XY), why dont we learn P(YX) directly?
Logistic Regression
Consider learning f: X
King Abdullah University of Science and Technology
analytics
CS 220

Fall 2016
CS220
Data Analytics
Midterm Exam, October 17, 2015
9am12noon
Name:
Student ID:
1.
2.
3.
4.
5.
There should be 10 pages including this cover page.
Closedbook exam. No books, notes, computers, phones, or internet access.
If you need more room to work out
King Abdullah University of Science and Technology
Data
CS 202

Fall 2016
HashBased Indexes
There are many possible implementations of hash indices. For the purposes of this class (e.g.
homeworks, exams, etc) we will assume the terminology and implementation from this book:
Database Management Systems 3ed, R. Ramakrishnan and