A primer slide for Big Data. Talks Basics. Gives Pointers.

1. Big Data
Introduction

2. Practical Examples
• Auto Suggestion in Google Search
• Google Translation
• Loui Von Ahn’s Re-CAPTCHA
• Completely Automated Public Turing Test to tell Computers and
Human Apart

3. Practical Examples
• Auto Tagging Photos
• Facebook
• Google Plus
• Google Image Search
• Twitter Follow Suggestions
• Flipkart, Amazon Product Recommendations

4. BigData in Sports
• Cricket
• Duckworth Lewis System
• Resources (wickets left and overs left)
• Target
• ODI: Runs at the end of 50 overs
• = double the runs @ 30 overs
• = 2.5 times runs @ 25 overs
• BaseBall
• Billy Beane and Paul DePodesta putting together a strong
baseball team with underdogs for 2002 American League
• ‘Moneyball’ book and movie

5. So, what is in it?
• Frame a question, analyze a large set of data to find patterns
and make predictions which serves as a possible answer to the
question.
• Improve upon.

6. What is the most important
component in BigData Analysis?
The DATA

7. What Else?
• Large Computing Power
• Efficient Algorithms
• Example: MapReduce
• File System tuned for large scale data
• HDFS
• Hive Data warehouse
• Statistical Analysis
• Correllation
• Regression
• Clustering
• Principal Component Analysis
• Discriminant Analysis
• Queuing
• ANOVA
• Hypothesis Testing
• Optimization Techniques
• Linear Programming
• Mixed Integer Programming
• Constraint Programming
MATHEMATICS

8. Closely Related Topics
• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• Learning Syntax and Semantics of Human Languages
• Data Analysis
• Algorithms

9. Turing Test
• Alan Turing (considered Father of Artificial Intelligence)
proposed a question “Can Machines Think?” in his 1950
research paper
• In a better way, if a question is asked, can a computer imitate
a human being and deceive the person who asked the
question, by making him believe the answer has come from a
human being instead of a computer.
• Rock Paper Scissors Game
• By Machine: http://www.nytimes.com/interactive/science/rock-
paper-scissors.html?_r=0

10. Difficult Tasks in Machine
Learning
• Judgement
• Taking decision with hypothetically contradictory outcomes.
• Responding to a new situation
• Natural Language Processing
• Understanding Syntax, Semantics
• Responding to Emotional Tones, Different Accents
• Imagination
• So, naturally story narration task is very difficult
• Concept of Truth / Good or Bad / Philosophy / Principles /
Ethics

11. In other words,
• Big Data Analysis - AI - Machine Learning
• Imparts “intelligence” into the computer.
• Makes it learn, one at a time.
• Improve the learning with new inputs and possible / expected /
realization of actual outputs.

12. Suggestions:
• Online Learning / Courses
• MOOC – Massively Open Online Courses
• Coursera
• edX
• Udacity
• Khan Academy
• Books / Movies
• Big Data: A Revolution That Will Transform How We Live, Work and
Think
• Viktor Mayer-Schonberger and Kenneth Cukier
• The Robot – 2010 Hindi / Tamil Movie
• Money Ball – 2011 Hollywood Movie (or 2003 book by Michael
Lewis)
• I Robot – 2004 Hollywood Movie

13. Where is this Content?
• http://www.slideshare.net/arunramatma