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MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari: • Algorithm: • Machine Learning: http

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Page 1: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http
Page 2: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 3: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

MACHINE LEARNING

Page 4: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 5: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http
Page 6: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 7: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Y = W · X ?

Page 8: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

NEURAL NETWORK

Page 9: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 10: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 11: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 12: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http
Page 13: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 14: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

DEEP LEARNING

Page 15: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 16: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 17: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

SUPERVISED LEARNING

Page 19: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

[r, g, b] [r][g][b]

Page 20: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 21: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Y = W · X ?

Page 22: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

FINDING WEIGHTS

Page 23: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

Page 25: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

FUNCTION FINDER

Page 26: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

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[email protected]

Page 32: MACHINE LEARNING - 삼성 오픈소스 컨퍼런스 · REFERENCES • Playing Atari:  • Algorithm:  • Machine Learning: http

REFERENCES

• Playing Atari: https://www.youtube.com/watch?v=V1eYniJ0Rnk

• Algorithm: https://wiki.python.org/moin/SimplePrograms

• Machine Learning: http://machinelearningmastery.com/basic-concepts-in-machine-learning/

• Universal Gate: http://gatedesignsnorit.blogspot.kr/2015/06/design-and-gate-using-2-1-mux.html

• CPU: https://www.intel.com/pressroom/archive/releases/2008/20081117comp_sm.htm

• Perceptron: http://www.fico.com/en/predictive-analytics/analytic-technologies/neural-networks

• Activation Function: https://en.wikipedia.org/wiki/Activation_function

• Multilayer Perceptron: http://stackoverflow.com/questions/5794954/determining-bias-for-neural-network-

perceptrons

• AlexNet: https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks

• Deep Learning Cat: https://cloud.google.com/blog/big-data/2016/07/understanding-neural-networks-with-

tensorflow-playground

• Neural Network Code: https://harthur.github.io/brain/

• Dimension: https://www.tensorflow.org/versions/r0.12/tutorials/mnist/beginners/index.html

• Weights: https://en.wikipedia.org/wiki/Mixing_console

• Learning to Swing: https://www.youtube.com/watch?v=q8i6wHCefU4

• TensorFlow Playground: http://playground.tensorflow.org/

• Fourier Transform: http://phys.org/news/2012-01-faster-than-fast-fourier.html

• Universal Approximation Theorem: https://www.youtube.com/watch?v=SahmdQs6X74

• WaveNet: https://deepmind.com/blog/wavenet-generative-model-raw-audio/

• Doom: https://www.youtube.com/watch?v=oo0TraGu6QY

• Google Data Centers: https://www.wired.com/2012/10/ff-inside-google-data-center/

• See You: https://www.nasa.gov/feature/jpl/an-insiders-guide-to-voyager-1977-2017/