Big Data Analytics and Applications презентация

Содержание

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Velocity Value Volume Variety

Velocity

Value

Volume

Variety

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Big Data are not data! Technology for gathering, storage, processing,

Big Data are not data!

Technology for gathering, storage, processing, and utilize
Method

of data processing and representation
Problem of resource lack
Social phenomenon
Data of big volume, variety, velocity, distributed
Big potential value
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Paradigm shift Subject of labour is not a program, but hypothesis and data

Paradigm shift

Subject of labour is not a program, but hypothesis and

data
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Paradigm shift More sources – higher veracity More data –

Paradigm shift

More sources – higher veracity
More data – higher accuracy
More data

– lower quality requirements
High-speed algorithms: O(N) or O(NlogN)
Unmovable data => parallelism and map reduce
Structure decline => information extraction
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2014

2014

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2015

2015

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Problems in Russian Big Data No depersonalization culture (FL-152) No

Problems in Russian Big Data

No depersonalization culture (FL-152)
No understanding of potential

value
Insufficient competence in statistics
Absence of data brokers
Highly risked data analytics projects
Lack of data
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Big Data education in Russia

Big Data education in Russia

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Master programs HSE: Big Data Systems Data Sciences MSU: «Intellectual

Master programs

HSE:
Big Data Systems
Data Sciences
MSU:
«Intellectual analysis of big data»
«Big Data: infrastructure

and solution technique»
NSU
Big Data Analytics
Computer modeling
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Online 1 week to 1 year Coursera, edX (http://rusbase.com/list/bigdatye-kursy/) Intuit (Introduction to Big Data Analytics) http://bit.ly/IntuitBDA

Online

1 week to 1 year
Coursera, edX (http://rusbase.com/list/bigdatye-kursy/)
Intuit (Introduction to Big

Data Analytics) http://bit.ly/IntuitBDA
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Additional education 1 week - 3 month - 2 years

Additional education

1 week - 3 month - 2 years
Yandex Data Analysis

School – https://yandexdataschool.ru/
Digital October – http://newprolab.ru
Beeline - http://bigdata.beeline.digital/datamba
Expasoft – http://expasoft.com/edu/
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NSU Big Data Strategy

NSU Big Data Strategy

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Syllabus of Master program

Syllabus of Master program

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Challenges 1st place, 2015, AVITO 1st place, 2015, eKapusta 4th

Challenges

1st place, 2015, AVITO
1st place, 2015, eKapusta
4th place among 619 teams,

2009, Data Mining Cup
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Skull surface restore No formulae No negative examples Neural networks, autoencoders

Skull surface restore

No formulae
No negative examples
Neural networks, autoencoders

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Deep learning Unsupervised

Deep learning

Unsupervised

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Semantic segmentation http://arxiv.org/pdf/1511.00561v2.pdf

Semantic segmentation

http://arxiv.org/pdf/1511.00561v2.pdf

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Van Gogh Ivan Gogov Alex J. Champandard. Semantic Style Transfer

Van Gogh Ivan Gogov

Alex J. Champandard. Semantic Style Transfer and Turning Two-Bit

Doodles into Fine Artworks. 2016
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Paintings http://tinyclouds.org/colorize/

Paintings

http://tinyclouds.org/colorize/

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Articles for revision http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Articles for revision

http://karpathy.github.io/2015/05/21/rnn-effectiveness/

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Pushkin A.I. Зафонствуя попруг, Ивисшивый чела, На воспопе днего, Я

Pushkin A.I.

Зафонствуя попруг, Ивисшивый чела, На воспопе днего, Я могина бесслужел, Катирей свети довой, Из увядебиле

меня, И на гразой шле, далодной Вольностью примстают; Я, водешил перцов миренья?

N.I. Putincev, stream data analytics and machine learning lab NSU

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