- https://docs.google.com/spreadsheets/d/18InS788sBL-napveBnIvh65Rf9GGpslL5rncM98bCm0/edit#gid=0
- 제출일자: TBA ([email protected]으로 제출)
- 제출형식: 발표자료 형식(PPT): 데이터 및 시각화, 데이터 전처리, 딥러닝 모델, 학습 및 테스트 결과, 결론 등
- (뉴런과 신경망 학습 코드) https://github.com/yungbyun/myml -> 구글 코랩(Google Colab)에서 실행하세요.
- (성별 인식 코드) https://www.kaggle.com/yungbyun/female-male-classification-ml-simple/edit/run/30600474 -> 캐글에서 바로 실행하세요.
- (식물생장) https://www.kaggle.com/code/yungbyun/plant-diary-original-simple -> 캐글에서 바로 실행하세요.
캐글 홈페이지를 방문하여 Iris 검색해보자. 그리고 아래의 검색되는 코드를 다운받은 후(Copy and Edit) 실행해보세요.
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import Adam
# 데이터
X = [1, 2, 3]
y = [1, 2, 3]
# 1개의 신경세포
gildong = Sequential()
neuron = Dense(1, input_dim=1, activation='linear')
gildong.add(neuron)
# 모델 컴파일
gildong.compile(optimizer=Adam(learning_rate=0.02), loss='mse')
# 학습
gildong.fit(X, y, epochs=1000, verbose=0)
# 예측/테스트
answer = gildong.predict(X)
print(f"Prediction: {answer}")
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실습(성별예측1): https://youtu.be/QBq2f_1gfZA
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실습(성별예측2): https://youtu.be/4IEbdh62d2Y
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실습(식물생장예측): https://youtu.be/DZnpkKxeB-w
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논리회귀1: https://youtu.be/vztm69wYlhs
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논리회귀2, https://youtu.be/gmEOiuB-TKM
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논리회귀3, https://youtu.be/greSudDm4Gc
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논리회귀4, https://youtu.be/z777NFDLNkQ
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논리회귀5, https://youtu.be/Tu9iyy4RaVo
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논리회귀6, https://youtu.be/Rl5bia3ts1U
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논리회귀7, https://youtu.be/LI6whxHBNT4
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논리회귀8, https://youtu.be/hqkNSTwrK9M
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논리회귀9, https://youtu.be/lhUFXIGhPEs
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논리회귀10, https://youtu.be/p6lLyh0G8RQ
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논리회귀11, https://youtu.be/IKpSvmsaDew
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논리회귀12, https://youtu.be/85hMwhKDSw4
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논리회귀13, https://youtu.be/2sAg8ze7K_U
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논리회귀14, https://youtu.be/GT9s4_f22TU
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논리회귀15, https://youtu.be/JGAjfgAGFkQ