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Python의 가능성 삼성 SDS 개발자 Conference OpeniT 5회 대안언어 축제 두산중공업 Software센터 조인석

Samsung SDS OpeniT - The possibility of Python

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Page 1: Samsung SDS OpeniT - The possibility of Python

Python의 가능성

삼성 SDS 개발자 Conference OpeniT 5회

대안언어 축제

두산중공업 Software센터

조 인 석

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Contents

Speaker is..

Python?

Why Python?

Java vs Python

Data Science w/ Python

How can I learn Python?

How can I play w/ Python?

Q & A

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Table of Contents

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조 인 석 (Chris Cho)

• 세종대 컴퓨터 공학 전공

• 육군전산소 SW개발병 (2년)

• 현대정보기술 해외금융개발팀 (7개월)

• 삼성 SDS (7년 3개월)

– ENG. Methodology 팀 & SI Process 팀 (2년 1개월)

• 통합 개발 플랫폼 대내외 프로젝트 지원

– Framework 팀 & Delivery Platform 팀 (5년 2개월)

• 삼성생명 차세대 Anyframe Enterprise BTO 전담 지원 (2년)

• 삼성전자 Global MES 2.0 Anyframe Enterprise 전담 지원 (3년)

• 두산 중공업 (현, 1년 9개월)

– Software센터 SW 개발팀

• Power & Water plant를 위한 Industrial IoT 관련 SW 개발 담당

• 실무환경에 맞춘 Node.js 프로그래밍 공저 (2014, 혜지원)

• 파이썬 입문 집필 중 (예정, 2016, 혜지원)

• Facebook : https://www.facebook.com/insuk.chris.cho

Speaker is..

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Python?

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Why Python? (1/4)

2015 Programming Language Rankings by RedMonk

Reference: http://redmonk.com/sogrady/2015/01/14/language-rankings-1-15/

Popularity Rank on GitHub

Popula

rity

Rank o

n S

tack O

verf

low

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Why Python? (2/4)

Most Popular Coding Languages of 2015

The result is based on hundreds of thousands of data points we've collected by processing over 600,000+ coding tests and challenges by over 2,000+ employers

Reference: http://blog.codeeval.com/codeevalblog/2015#.VZDg-PntlBc

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Why Python? (3/4)

You can find Python everywhere..

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Why Python? (4/4)

You can find Python everywhere..

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Java vs Python

Reference: http://www.javascriptstyle.com/java-vs-python

• //

– //

• //

– //

• //

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Python IDE – Jupyter (iPython-notebook)

Using Web Browser

Explanation

(Comments)

Source Code

Execution Results

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Data volume is growing exponentially within companies. Most don't know how to harvest its value or how to even compute on it.

Growing mess of tools, databases, and products. New products increase integration headaches, instead of simplifying.

New hardware & architectures are tempting, but are avoided or sit idle because of software challenges.

Promises of the "Big Red Solve" button continue to disappoint. (If someone can give you this button, they are your competitor.)

Data Science w/ Python (1/5)

※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU

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Data Science w/ Python (2/5)

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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU

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Data Science w/ Python (3/5)

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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU

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Data Science w/ Python (4/5)

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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU

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Data Science w/ Python (5/5)

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OpenOPC for Python (http://openopc.sourceforge.net/)- OpenOPC for Python is a free, open source OPC (OLE for Process Control) toolkit

designed for use with the popular Python programming language

MQTT Brocker - Mosquitto (http://mosquitto.org/)

- Mosquitto makes it suitable for "machine to machine" messaging such as with low power sensors or mobile devices such as phones, embedded computers or microcontrollers

MQTT Client – paho-mqtt (https://pypi.python.org/pypi/paho-mqtt)- This code provides a client class which enable applications to connect to an MQTT

broker to publish messages, and to subscribe to topics and receive published messages

NumPy (http://www.numpy.org/, http://en.wikipedia.org/wiki/NumPy)- an optimized python library for numerical analysis, specifically: large, multi-

dimensional arrays and matrices. Found in Introduction to Data Science Pandas (http://pandas.pydata.org/, http://en.wikipedia.org/wiki/Pandas_(software) )

- an optimized python library for data analysis including dataframes inspired by R. Found in Introduction to Data Science

SciKit-learn (http://scikit-learn.org/stable/, http://en.wikipedia.org/wiki/Scikit-learn)- machine learning library built on NumPy, SciPy, and matplotlib. Mentioned in

Introduction to Machine Learning H2O (http://h2o.ai/)

- H2O is for data scientists and application developers who need fast, in-memory scalable machine learning for smarter applications. H2O is an open source parallel processing engine for machine learning

Django (https://www.djangoproject.com/)- Django is a high-level Python Web framework that encourages rapid development

and clean, pragmatic design

Anaconda (http://continuum.io/downloads)- a python package manager with the intent of simplifying and maintaining compatibility

between library versions. Also useful for getting started with ipython notebooks

Data Gathering

Data Distribution

& Sharing

Data Learning

& Modeling

Visualization

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How can I learn Python? –www.edx.org

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How can I learn Python? –www.microsoftvirtaulacademy.com

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How can I play w/ Python? –www.codecademy.com

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How can I play w/ Python? –www.hackerrank.com

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Q & A