Talk by Michael Krech (@Parsec) held during the Open Data Meetup in Frankfurt: http://www.meetup.com/de/OKLabFfm/events/219667158/

1. Brief Introduction to
Machine Learning
Michael Krech, @Parsec

2. @Parsec A brief introduction to Machine Learning
OUR MISSION
Chapter 1: History - Present
Chapter 2: Overview
Chapter 3: Computer can ..
Chapter 4: Why now?
Chapter 5: Future

3. @Parsec A brief introduction to Machine Learning
CHAPTE
R
1

4. @Parsec A brief introduction to Machine Learning
HISTORY

5. @Parsec A brief introduction to Machine Learning
PRESENT

6. @Parsec A brief introduction to Machine Learning
PRESENT

7. @Parsec A brief introduction to Machine Learning
PRESENT
What are my recommended
movies ?

8. @Parsec A brief introduction to Machine Learning
PRESENT
What are my recommended friends?

9. @Parsec A brief introduction to Machine Learning
PRESENT
https://www.youtube.com/watch?v=YgYSv2KSyWg
In initial tests run during 2006 by David Ferrucci, the senior manager of IBM's
Semantic Analysis and Integration department,Watson was given 500 clues from
past Jeopardy! programs.
While the best real-life competitors buzzed in half the time and responded
correctly to as many as 95% of clues,Watson's first pass could get only about 15%
correct. During 2007, the IBM team was given three to five years and a staff of 15
people to solve the problems.
By 2008, the developers had advanced Watson such that it could compete with
Jeopardy! Champions. By February 2010,Watson could beat human Jeopardy!
contestants on a regular basis

10. @Parsec A brief introduction to Machine Learning
PRESENT
In June 2015, the team announced that their vehicles have now driven over 1
million miles, stating that this was "the equivalent of 75 years of typical U.S.
adult driving", and that in the process they had encountered 200,000 stop
signs, 600,000 traffic lights, and 180 million other vehicles. Google also
announced its prototype vehicles were being road tested in MountainView,
California.
During testing, the prototypes' speed cannot exceed 25 mph and will have
safety drivers aboard the entire time.

11. @Parsec A brief introduction to Machine Learning
CHAPTE
R
2

12. @Parsec A brief introduction to Machine Learning
OVERVIEW

13. @Parsec A brief introduction to Machine Learning
2,5 KINDS OF MACHINE LEARNING
ALGORITHMS
Supervised Learning
Unsupervised Learning
Reinforcement learning

14. @Parsec A brief introduction to Machine Learning
SUPERVISED-LEARNING
Supervised learning is the machine learning task of inferring a
function from labeled training data. The training data consist
of a set of training examples.
In supervised learning, each example is a pair consisting of an
input object (typically a vector) and a desired output value
(also called the supervisory signal). A supervised learning
algorithm analyzes the training data and produces an inferred
function, which can be used for mapping new examples.
An optimal scenario will allow for the algorithm to correctly
determine the class labels for unseen instances. This requires
the learning algorithm to generalize from the training data to
unseen situations in a "reasonable" way

15. @Parsec A brief introduction to Machine Learning
UNSUPERVISED LEARNING
In machine learning, the problem of unsupervised learning is that of
trying to find hidden structure in unlabeled data. Since the examples
given to the learner are unlabeled, there is no error or reward signal to
evaluate a potential solution. This distinguishes unsupervised learning
from supervised learning and reinforcement learning.
Unsupervised learning is closely related to the problem of density
estimation in statistics.
However unsupervised learning also encompasses many other
techniques that seek to summarize and explain key features of the
data. Many methods employed in unsupervised learning are based on
data mining methods used to preprocess[citation needed] data.
e.g.: Anomaly detection …

16. @Parsec A brief introduction to Machine Learning
REINFORMENT-LEARNING,
(SEMI-SUPERVISED)
Reinforcement learning is an area of machine learning
inspired by behaviorist psychology, concerned with
how software agents ought to take actions in an
environment so as to maximize some notion of
cumulative reward.
This is the most common form, humans learn.

17. @Parsec A brief introduction to Machine Learning
REINFORMENT-LEARNING,
(SEMI-SUPERVISED)
http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html

18. @Parsec A brief introduction to Machine Learning
WORKSPACES
Reporting
Search
Exploration
Prediction
Classification

19. @Parsec A brief introduction to Machine Learning
CHAPTE
R
3

20. @Parsec A brief introduction to Machine Learning
COMPUTER CAN ….
?

21. @Parsec A brief introduction to Machine Learning
LISTEN, SPEAK
https://www.youtube.com/watch?v=Nu-nlQqFCKg
Speech Recognition Breakthrough for the
Spoken, Translated Word

22. @Parsec A brief introduction to Machine Learning
SEE
http://benchmark.ini.rub.de/?section=gtsrb&subsection=results
Computer better as humans

23. @Parsec A brief introduction to Machine Learning
RECOGNITION
Google can identify and transcribe all the views it has of street numbers in
France in less than an hour, thanks to a neural network that’s just as good as
human operators.
http://www.technologyreview.com/view/523326/how-google-cracked-house-
number-identification-in-street-view/
Wie lange und wie viele Menschen hätte dies benötigt?

24. @Parsec A brief introduction to Machine Learning
RECOGNITON AND CLUSTER
A selection of evaluation results, grouped by human rating.
http://googleresearch.blogspot.in/2014/11/a-picture-is-worth-thousand-
coherent.html

25. @Parsec A brief introduction to Machine Learning
SING
https://www.youtube.com/watch?v=dKUDHPw15m0

26. @Parsec A brief introduction to Machine Learning
READ
OCR
http://de.wikipedia.org/wiki/Texterkennung

27. @Parsec A brief introduction to Machine Learning
UNDERSTAND
http://nlp.stanford.edu/sentiment/
http://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf

28. @Parsec A brief introduction to Machine Learning
COMPUTER CAN …
Read &
Write
Listen,
Speak
Singen
See,
Recognition
Understand

29. @Parsec A brief introduction to Machine Learning
CHAPTE
R
4

30. @Parsec A brief introduction to Machine Learning
WHY THIS WORKS BETTER NOW
CLOUD / CLUSTER / CORES TOOLS Technologies (Forbes)
GPU, SaaS, PaaS,
IaaS, Amazon Cloud
Computing, Google
Cloud Computing ….
Hadoop, Spark,
Elasticsearch,
MongoDB, Neo4j,
Mahout, Python, R
Deep Learning,
Clustering, Anomaly
Detection, ConvNet,
Reinforcement, Statistics

31. @Parsec A brief introduction to Machine Learning
BIOLOGIC PYRAMID
@mike_schatz

32. @Parsec A brief introduction to Machine Learning
CHAPTE
R
5

33. @Parsec A brief introduction to Machine Learning
Moores Law, complexity
of IC’s double’s in 12-24 Month

34. @Parsec A brief introduction to Machine Learning
T-1000
http://en.wikipedia.org/wiki/T-1000

35. @Parsec A brief introduction to Machine Learning
TURING TEST
Back in 2002 Kurzweil (a scientist
renowned for his accurate tech
predictions), bet Mitch Kapor (founder of
Lotus Development Corp., inventor of
spreadsheet software) $20,000 that a
computer would pass the Turing Test by
2029.
He predicts a Singularity for the yeaar
2045….
Er prognostiziert für das Jahr 2045 eine
exponentielle Zunahme der
informationstechnologischen Entwicklung:
Eine Singularität, die eine künstliche
Intelligenz ermöglicht, mit welcher die
Menschheit Unsterblichkeit erlangen kann.
https://en.wikipedia.org/wiki/
Predictions_made_by_Ray_Kurzweil#204
5:_The_Singularity
(Wikipedia)
Alan Turing Ray Kurzweil
Raymond "Ray" Kurzweil is an American author, computer
scientist, inventor, futurist, and is a director of engineering at
Google. Aside from futurology, he is involved in fields such
as optical character recognition (OCR), text-to-speech
synthesis, speech recognition technology, and electronic
keyboard instruments. He has written books on health,
artificial intelligence (AI), transhumanism, the technological
singularity, and futurism. Kurzweil is a public advocate for
the futurist and transhumanist movements, as has been
displayed in his vast collection of public talks, wherein he
has shared his primarily optimistic outlooks on life extension
technologies and the future of nanotechnology, robotics, and
biotechnology.
The Turing test was introduced by
Alan Turing in 1950. The Turing
test is a test of a machine's ability
to exhibit intelligent behavior
equivalent to, or indistinguishable
from, that of a human.

36. THANK YOU