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RNN
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custom_data
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docker
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CONTRIBUTING.md
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README.md
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data-01-test-score.csv
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docker_user_guide.md
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lab-01_tensor_manipulation.ipynb
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lab-02_linear_regression.ipynb
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lab-03_minimizing_cost.ipynb
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lab-04_1_multivariable_linear_regression.ipynb
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lab-04_2_load_data.ipynb
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lab-05_logistic_classification.ipynb
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lab-06_1_softmax_classification.ipynb
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lab-06_2_fancy_softmax_classification.ipynb
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lab-07_1_tips.ipynb
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lab-07_2_mnist_introduction.ipynb
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lab-08_1_xor.ipynb
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lab-08_2_xor_nn.ipynb
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lab-08_3_xor_nn_wide_deep.ipynb
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lab-08_4_mnist_back_prop.ipynb
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lab-09_1_mnist_softmax.ipynb
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lab-10_6_1_Advance-CNN(Resnet).ipynb
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lab-11_4_timeseries.ipynb
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lab-11_5_seq2seq.ipynb
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lab-11_6_PackedSequence.ipynb
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requirements.txt
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resnet.py
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run_jupyter_docker.sh
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vgg.py
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๋ชจ๋‘๋ฅผ ์œ„ํ•œ ๋”ฅ๋Ÿฌ๋‹ ์‹œ์ฆŒ2 : ๋ชจ๋‘๊ฐ€ ๋งŒ๋“œ๋Š” ๋ชจ๋‘๋ฅผ ์œ„ํ•œ ๋”ฅ๋Ÿฌ๋‹

๋ชจ๋‘๊ฐ€ ๋งŒ๋“œ๋Š” ๋ชจ๋‘๋ฅผ ์œ„ํ•œ ๋”ฅ๋Ÿฌ๋‹ ์‹œ์ฆŒ 2์— ์˜ค์‹  ์—ฌ๋Ÿฌ๋ถ„๋“ค ํ™˜์˜ํ•ฉ๋‹ˆ๋‹ค.

Getting Started

์•„๋ž˜ ๋งํฌ์—์„œ ์Šฌ๋ผ์ด๋“œ์™€ ์˜์ƒ์„ ํ†ตํ•ด ํ•™์Šต์„ ์‹œ์ž‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Docker ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•œ ์•ˆ๋‚ด

๋™์ผํ•œ ์‹ค์Šต ํ™˜๊ฒฝ์„ ์œ„ํ•ด docker ๋ฅผ ์‚ฌ์šฉํ•˜์‹ค ๋ถ„์€ docker_user_guide.md ํŒŒ์ผ์„ ์ฐธ๊ณ ํ•˜์„ธ์š”! :)

Install Requirements

pip install -r requirements.txt

Install PyTorch from website: https://pytorch.org/

PyTorch

Deep Learning Zero to All - PyTorch

๋ชจ๋“  ์ฝ”๋“œ๋Š” PyTorch 1.0.0 ๊ธฐ์ค€์œผ๋กœ ์ž‘์„ฑํ•˜์˜€์Šต๋‹ˆ๋‹ค.

Contributions/Comments

์–ธ์ œ๋‚˜ ์—ฌ๋Ÿฌ๋ถ„๋“ค์˜ ์ฐธ์—ฌ๋ฅผ ํ™˜์˜ํ•ฉ๋‹ˆ๋‹ค. Comments๋‚˜ Pull requests๋ฅผ ๋‚จ๊ฒจ์ฃผ์„ธ์š”

We always welcome your comments and pull requests

๋ชฉ์ฐจ

PART 1: Machine Learning & PyTorch Basic

  • Lab-01-1 Tensor Manipulation 1
  • Lab-01-2 Tensor Manipulation 2
  • Lab-02 Linear regression
  • Lab-03 Deeper Look at GD
  • Lab-04-1 Multivariable Linear regression
  • Lab-04-2 Loading Data
  • Lab-05 Logistic Regression
  • Lab-06 Softmax Classification
  • Lab-07-1 Tips
  • Lab-07-2 MNIST Introduction

PART 2: Neural Network

  • Lab-08-1 Perceptron
  • Lab-08-2 Multi Layer Perceptron
  • Lab-09-1 ReLU
  • Lab-09-2 Weight initialization
  • Lab-09-3 Dropout
  • Lab-09-4 Batch Normalization

PART 3: Convolutional Neural Network

  • Lab-10-0 Convolution Neural Networkintro
  • Lab-10-1 Convolution
  • Lab-10-2 mnist cnn
  • Lab-10-3 visdom
  • Lab-10-4-1 ImageFolder1
  • Lab-10-4-2 ImageFolder2
  • Lab-10-5 Advance CNN(VGG)
  • Lab-10-6-1 Advanced CNN(RESNET-1)
  • Lab-10-6-2 Advanced CNN(RESNET-2)
  • Lab-10-7 Next step of CNN

PART 4: Recurrent Neural Network

  • Lab-11-0 RNN intro
  • Lab-11-1 RNN basics
  • Lab-11-2 RNN hihello and charseq
  • Lab-11-3 Long sequence
  • Lab-11-4 RNN timeseries
  • Lab-11-5 RNN seq2seq
  • Lab-11-6 PackedSequence

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