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πŸ“— λͺ¨λ‘μ˜ λ”₯λŸ¬λ‹ (2판, μ‘°νƒœν˜Έ)

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#01_My_First_DL
#01_My_First_DL
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#03_Linear_Regression
#03_Linear_Regression
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#04_Gradient_Descent
#04_Gradient_Descent
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#05_Logistic_Regression
#05_Logistic_Regression
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#07_Multilayer_Perceptron
#07_Multilayer_Perceptron
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#10_Model_Design
#10_Model_Design
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#11_Data_Handling
#11_Data_Handling
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#12_Multi_Classification
#12_Multi_Classification
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#13_Avoid_Overfitting
#13_Avoid_Overfitting
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#14_Make_Best_Model
#14_Make_Best_Model
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#15_DNN_with_Linear_Regression
#15_DNN_with_Linear_Regression
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#16_CNN
#16_CNN
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#17_NLP
#17_NLP
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#18_RNN
#18_RNN
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#19_GAN_and_Auto_Encoder
#19_GAN_and_Auto_Encoder
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#20_Transfer_Learning
#20_Transfer_Learning
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#Advanced_Contents
#Advanced_Contents
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dataset
dataset
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README.md
README.md
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πŸ“—Keras_TF_Deep_Learning

πŸ‘‰ λͺ¨λ‘μ˜ λ”₯λŸ¬λ‹ (2판, μ‘°νƒœν˜Έ)

μ„œμ  이미지

  • λ”₯λŸ¬λ‹ κΈ°λ³Έ ꡬ성 원리에 λŒ€ν•΄ 비ꡐ적 μ‰½κ²Œ ν’€μ–΄μ“΄ 편이라 μž…λ¬Έ 단계 μ‹œμ ˆλΆ€ν„° 자주 μ• λ…ν•˜μ˜€μŒ.
  • λ‹€μ–‘ν•œ μ‹€μ œ 데이터 μ˜ˆμ œμ™€ ν•¨κ»˜ μ—¬λŸ¬ λ”₯λŸ¬λ‹ λͺ¨λΈ(DNN, CNN, RNN, LSTM, GAN, AutoEncoder λ“±)을 λ‹€λ£Έ.
  • ν…μ„œν”Œλ‘œ μœ„μ—μ„œ μΌ€λΌμŠ€κ°€ μ–΄λ–€ μ‹μœΌλ‘œ λ™μž‘ν•˜λŠ”μ§€ μ•Œμ•„λ³΄λŠ” μš©λ„λ‘œ μ’‹μŒ.
  • Tensorflow μ—…λ°μ΄νŠΈ 문제 λ•Œλ¬Έμ— 개인적으둜 μ½”λ“œ μˆ˜μ •ν•˜λŠ” 단계λ₯Ό 거쳀음.

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