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Introduction to Big Data

Date post: 22-Nov-2014
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Description:
A primer slide for Big Data. Talks Basics. Gives Pointers.
13
Big Data Introduction
Transcript
Page 1: Introduction to Big Data

Big DataIntroduction

Page 2: Introduction to Big Data

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

Page 3: Introduction to Big Data

Practical Examples• Auto Tagging Photos• Facebook• Google Plus• Google Image Search

• Twitter Follow Suggestions• Flipkart, Amazon Product Recommendations

Page 4: Introduction to Big Data

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

Page 5: Introduction to Big Data

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.

Page 6: Introduction to Big Data

What is the most important component in BigData Analysis?

The DATA

Page 7: Introduction to Big Data

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

MATHEM

ATICS

Page 8: Introduction to Big Data

Closely Related Topics• Artificial Intelligence• Machine Learning• Natural Language Processing• Learning Syntax and Semantics of Human Languages

• Data Analysis• Algorithms

Page 9: Introduction to Big Data

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

Page 10: Introduction to Big Data

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

Page 11: Introduction to Big Data

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.

Page 12: Introduction to Big Data

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

Page 13: Introduction to Big Data

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


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