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오픈소스로
시작하는
인공지능 실습
Artificial Intelligence
practice starting with
open source
중앙대학교 의료보안연구소
Mario Cho (조만석)
hephaex@gmail....
Mario Cho
Development Experience
◆ Image Recognition using Neural Network
◆ Bio-Medical Data Processing
◆ Human Brain Mapp...
What is the Machine Learning ?
• Field of Computer Science that evolved from the
study of pattern recognition and computat...
Neural network vs Learning network
Neural Network Deep Learning Network
Neural Network as a Computational Graph
• In Most Machine Learning Frameworks,
• Neural Network is conceptualized as a
Com...
Tensorflow Computational Graph
Tensor
(다차원행렬)
Tensor Tensor
곱셈
덧셈
함수
Tensor: 3차 이상 다차원 행렬
Single layer perceptron
Affine ReLUX
W b
h1 C
Multi layer perceptron
X
W1 b1
h1Affine
a1
W2 b2
h2Affine
ReLU
ReLU
a2
W3 b3
h3Affine Softmax
t
Cross
Entropy
prob loss
What is a neural network?
Yes/No
(Mug or not?)
Data (image)
!
x1
∈!5
,!x2
∈!5
x2
=(W1
×x1
)+
x3
=(W2
×x2
)+
x1 x2 x3
x4
x5...
Deep learning : CNN
Make predictions on data
Deep Learning Framework comparison
출처: Getting Started with Dep Learning
https://svds.com/getting-started-deep-learning/
GPU
Tensor Operation in GPU
Tensor Core : NVIDIA Volta
NVIDIA Volta Architecture
Comparison of NVIDIA GPUs
Nvidia GPU Roadmap
AMD GPU road map
Tensorflow Processing Unit (TPU)
AlphaGo Gen1
Machine Learning Farm
Why is Deep Learning taking off?
Engine
Fuel
Large neural networks
Labeled data
(x,y pairs)
Google S/W Projects
History of Deep Learning Framework
2010
2013
2014
2015
2016
2017
(Nov.)
(Dec.)
(Jul.)
(Jun.)
On GitHub
(Debut: Apr. ‘2015)...
Google Tensorflow
I. Setup Virtual Environment
• Virtual Box 5.1 Download & install.
• https://www.virtualbox.org
I. Setup Virtual Environment
• VirtualBox 5.1.22 for Windows hosts x86/amd64
• VirtualBox 5.1.22 for OS X hosts amd64
II. Operating System: download
• http://releases.ubuntu.com/
• http://releases.ubuntu.com/xenial/
II. Operating System: download
• https://launchpad.net/ubuntu/+mirror/ftp.daum.net-release
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: virtual box setup
II. Operating System: ready to install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
II. Operating System: install
III. Setting Network
• $ sudo nano /etc/network/interfaces
– 네트워크 장치 정보를 입력하고 CTRL+X로 저장
• $ sudo reboot
III. SSH server install
• 설치를 안했을 경우 새로 설치
• $ sudo apt-get install openssh-server
• 검증 verify
• $ sudo service ssh status
III. install local terminal
• http://www.putty.org 에 접속해서
III. install local terminal
• http://www.putty.org 에 접속해서
III. install local terminal
III. install local terminal
III. install local terminal
III. Open local terminal using putty or term
• Windows 환경: putty 를 설치하고, 창을 열어 192.168.56.10 으로 접속합니다.
• OSX 환경: 터미널을 열어 $...
III. Repository update
• $ sudo apt-get update && sudo apt-get dist-upgrade
IV. Install docker
• $ wget -qO- https://get.docker.com/ | sh
• $ sudo usermod -aG docker ubuntu
V. Execute dev. Based on web.
• $ $ docker run -it -p 8888:8888 hephaex/tensorflow:1.1.0
– 텐서 플로우 1.1.0 버전과 표준 사용 예제가 설치된 ...
V. Execute dev. Based on web.
• 웹브라우져 (IE, Chrome, Sapari, FireFox, , , etc)
• http://192.168.56.10:8888
• 패드워드 : tensorfl...
Vi. Tutorial #1: hello world
Vi. Tutorial #1: install pip package
Vi. Tutorial #1 : Hello TensorFlow
Vi. Tutorial #1 : add operation
Vi. Tutorial #1 : loop
iX. Tutorial #2 matrix multiplication
iX. Tutorial #2 matrix multiplication
iX. Tutorial #2 matrix multiplication
IX. Tutorial #3 word2vector
IX. Tutorial #3 word2vector
IX. Tutorial #3 word2vector
IX. Tutorial #3 word2vector
IX. Tutorial #3 word2vector
IX. Tutorial #3 word2vector
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
X. Tutorial #4 data representation
XI. Tutorial #5 Linear regression
XI. Tutorial #5 Linear regression
XI. Tutorial #5 Linear regression
XI. Tutorial #5 Linear regression
XII. Tutorial #6 MNIST: Image recognition in Google Map
* Source: Oriol Vinyals – Research Scientist at Google Brain
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST: data set
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
XII. Tutorial #6 MNIST
Challenges Computing
Thanks you!
Q&A
오픈소스로 시작하는 인공지능 실습
오픈소스로 시작하는 인공지능 실습
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오픈소스로 시작하는 인공지능 실습

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대표적인 인공지능 프레임 워크인 텐서플로우를 설치부터 실습까지 설명하는 자료입니다.
인공지능에 관심 있는 분들이 처음부터 시작할 수 있는 마중물이 되었으면 하는 바램입니다.
본 자료는 ETRI 인공 지능 실습에 사용되었습니다.

저작물에 저작권은 원 사용자에게 있습니다.

Published in: Software
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오픈소스로 시작하는 인공지능 실습

  1. 1. 오픈소스로 시작하는 인공지능 실습 Artificial Intelligence practice starting with open source 중앙대학교 의료보안연구소 Mario Cho (조만석) hephaex@gmail.com
  2. 2. Mario Cho Development Experience ◆ Image Recognition using Neural Network ◆ Bio-Medical Data Processing ◆ Human Brain Mapping on High Performance Computing ◆ Medical Image Reconstruction (Computer Tomography) ◆ Enterprise System ◆ Open Source Software Developer ◆ OPNFV (NFV&SDN) & OpenStack ◆ Machine Learning (TensorFlow, Torch, Leaf) Cognitive Artificial Intelligence for Medicine ◆ Machine Learning ◆ Medical Informatics of oncology Book ◆ Unix V6 Kernel Chung-Ang University Mario Cho hephaex@gmail.com
  3. 3. What is the Machine Learning ? • Field of Computer Science that evolved from the study of pattern recognition and computational learning theory into Artificial Intelligence. • Its goal is to give computers the ability to learn without being explicitly programmed. • For this purpose, Machine Learning uses mathematical / statistical techniques to construct models from a set of observed data rather than have specific set of instructions entered by the user that define the model for that set of data.
  4. 4. Neural network vs Learning network Neural Network Deep Learning Network
  5. 5. Neural Network as a Computational Graph • In Most Machine Learning Frameworks, • Neural Network is conceptualized as a Computational Graph • The simple form of Computational Graph, • Directed Acyclic Graph consist Data Nodes and Operator Nodes Y = x1 * x2 Z = x3 – y Data node Opeator node
  6. 6. Tensorflow Computational Graph Tensor (다차원행렬) Tensor Tensor 곱셈 덧셈 함수 Tensor: 3차 이상 다차원 행렬
  7. 7. Single layer perceptron Affine ReLUX W b h1 C
  8. 8. Multi layer perceptron X W1 b1 h1Affine a1 W2 b2 h2Affine ReLU ReLU a2 W3 b3 h3Affine Softmax t Cross Entropy prob loss
  9. 9. What is a neural network? Yes/No (Mug or not?) Data (image) ! x1 ∈!5 ,!x2 ∈!5 x2 =(W1 ×x1 )+ x3 =(W2 ×x2 )+ x1 x2 x3 x4 x5 W4W3W2W1
  10. 10. Deep learning : CNN
  11. 11. Make predictions on data
  12. 12. Deep Learning Framework comparison 출처: Getting Started with Dep Learning https://svds.com/getting-started-deep-learning/
  13. 13. GPU
  14. 14. Tensor Operation in GPU
  15. 15. Tensor Core : NVIDIA Volta
  16. 16. NVIDIA Volta Architecture
  17. 17. Comparison of NVIDIA GPUs
  18. 18. Nvidia GPU Roadmap
  19. 19. AMD GPU road map
  20. 20. Tensorflow Processing Unit (TPU)
  21. 21. AlphaGo Gen1
  22. 22. Machine Learning Farm
  23. 23. Why is Deep Learning taking off? Engine Fuel Large neural networks Labeled data (x,y pairs)
  24. 24. Google S/W Projects
  25. 25. History of Deep Learning Framework 2010 2013 2014 2015 2016 2017 (Nov.) (Dec.) (Jul.) (Jun.) On GitHub (Debut: Apr. ‘2015) (Oct.) (Jun.) (Nov.) (Jan.) (Apr.) (Mar.)
  26. 26. Google Tensorflow
  27. 27. I. Setup Virtual Environment • Virtual Box 5.1 Download & install. • https://www.virtualbox.org
  28. 28. I. Setup Virtual Environment • VirtualBox 5.1.22 for Windows hosts x86/amd64 • VirtualBox 5.1.22 for OS X hosts amd64
  29. 29. II. Operating System: download • http://releases.ubuntu.com/ • http://releases.ubuntu.com/xenial/
  30. 30. II. Operating System: download • https://launchpad.net/ubuntu/+mirror/ftp.daum.net-release
  31. 31. II. Operating System: virtual box setup
  32. 32. II. Operating System: virtual box setup
  33. 33. II. Operating System: virtual box setup
  34. 34. II. Operating System: virtual box setup
  35. 35. II. Operating System: virtual box setup
  36. 36. II. Operating System: virtual box setup
  37. 37. II. Operating System: virtual box setup
  38. 38. II. Operating System: virtual box setup
  39. 39. II. Operating System: ready to install
  40. 40. II. Operating System: install
  41. 41. II. Operating System: install
  42. 42. II. Operating System: install
  43. 43. II. Operating System: install
  44. 44. II. Operating System: install
  45. 45. II. Operating System: install
  46. 46. II. Operating System: install
  47. 47. II. Operating System: install
  48. 48. II. Operating System: install
  49. 49. II. Operating System: install
  50. 50. II. Operating System: install
  51. 51. II. Operating System: install
  52. 52. II. Operating System: install
  53. 53. II. Operating System: install
  54. 54. II. Operating System: install
  55. 55. II. Operating System: install
  56. 56. II. Operating System: install
  57. 57. II. Operating System: install
  58. 58. II. Operating System: install
  59. 59. II. Operating System: install
  60. 60. II. Operating System: install
  61. 61. II. Operating System: install
  62. 62. III. Setting Network • $ sudo nano /etc/network/interfaces – 네트워크 장치 정보를 입력하고 CTRL+X로 저장 • $ sudo reboot
  63. 63. III. SSH server install • 설치를 안했을 경우 새로 설치 • $ sudo apt-get install openssh-server • 검증 verify • $ sudo service ssh status
  64. 64. III. install local terminal • http://www.putty.org 에 접속해서
  65. 65. III. install local terminal • http://www.putty.org 에 접속해서
  66. 66. III. install local terminal
  67. 67. III. install local terminal
  68. 68. III. install local terminal
  69. 69. III. Open local terminal using putty or term • Windows 환경: putty 를 설치하고, 창을 열어 192.168.56.10 으로 접속합니다. • OSX 환경: 터미널을 열어 $ ssh 192.168.56.10 –l ubuntu 로 접속합니다.
  70. 70. III. Repository update • $ sudo apt-get update && sudo apt-get dist-upgrade
  71. 71. IV. Install docker • $ wget -qO- https://get.docker.com/ | sh • $ sudo usermod -aG docker ubuntu
  72. 72. V. Execute dev. Based on web. • $ $ docker run -it -p 8888:8888 hephaex/tensorflow:1.1.0 – 텐서 플로우 1.1.0 버전과 표준 사용 예제가 설치된 도커 이미지 • $ docker run -it -p 8888:8888 hephaex/tensorflow:etri – 텐서 플로우 1.1.0 버전과 실습에 사용된 예제가 설치된 도커 이미지
  73. 73. V. Execute dev. Based on web. • 웹브라우져 (IE, Chrome, Sapari, FireFox, , , etc) • http://192.168.56.10:8888 • 패드워드 : tensorflow
  74. 74. Vi. Tutorial #1: hello world
  75. 75. Vi. Tutorial #1: install pip package
  76. 76. Vi. Tutorial #1 : Hello TensorFlow
  77. 77. Vi. Tutorial #1 : add operation
  78. 78. Vi. Tutorial #1 : loop
  79. 79. iX. Tutorial #2 matrix multiplication
  80. 80. iX. Tutorial #2 matrix multiplication
  81. 81. iX. Tutorial #2 matrix multiplication
  82. 82. IX. Tutorial #3 word2vector
  83. 83. IX. Tutorial #3 word2vector
  84. 84. IX. Tutorial #3 word2vector
  85. 85. IX. Tutorial #3 word2vector
  86. 86. IX. Tutorial #3 word2vector
  87. 87. IX. Tutorial #3 word2vector
  88. 88. X. Tutorial #4 data representation
  89. 89. X. Tutorial #4 data representation
  90. 90. X. Tutorial #4 data representation
  91. 91. X. Tutorial #4 data representation
  92. 92. X. Tutorial #4 data representation
  93. 93. X. Tutorial #4 data representation
  94. 94. X. Tutorial #4 data representation
  95. 95. X. Tutorial #4 data representation
  96. 96. XI. Tutorial #5 Linear regression
  97. 97. XI. Tutorial #5 Linear regression
  98. 98. XI. Tutorial #5 Linear regression
  99. 99. XI. Tutorial #5 Linear regression
  100. 100. XII. Tutorial #6 MNIST: Image recognition in Google Map * Source: Oriol Vinyals – Research Scientist at Google Brain
  101. 101. XII. Tutorial #6 MNIST
  102. 102. XII. Tutorial #6 MNIST: data set
  103. 103. XII. Tutorial #6 MNIST
  104. 104. XII. Tutorial #6 MNIST
  105. 105. XII. Tutorial #6 MNIST
  106. 106. XII. Tutorial #6 MNIST
  107. 107. XII. Tutorial #6 MNIST
  108. 108. XII. Tutorial #6 MNIST
  109. 109. XII. Tutorial #6 MNIST
  110. 110. Challenges Computing
  111. 111. Thanks you! Q&A

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