공부 기록

daterutil : 날짜 관련 matplotlib.ticker: 그래프의 눈금 위치, 형식 지정 모듈 MaxNLocator: 좋은 위치에 눈금이 있는 최대 간격을 찾습니다. FormatStrFormatter: 문자열로 라벨을 설정합니다. PercentFormatter: 백분율로 라벨을 설정합니다. sklearn.compose.TranformedTargetRegressor: 회귀에서 데이터를 변환해 분포를 고르게 한 후, 예측할 때 값을 역변환해야하는데, 그걸 수행해주는 라이브러리 DataFrame.unstack(level): level을 열로 하게끔 DataFrame을 재구성 ndarrat.squeeze(): ndarray의 필요 없는 축을 제거한다. >>> x = np.array([[[0], [1],..

import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns import gc import warnings warnings.filterwarnings('ignore') from sklearn.model_selection import train_test_split from sklearn.model_selection import cross_val_score train = pd.read_csv(train_path) test = pd.read_csv(test_path) !pip install pycaret --user # Unique train.num_sold.value_counts() ''' 189 99 ..

import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt # import warnings import warnings # filter warnings warnings.filterwarnings('ignore') train = pd.read_csv('/content/drive/MyDrive/military/mnist/train.csv') print(train.shape) train.head() ''' 결과1 ''' # put labels into y_train variable Y_train = train['label'] # Drop 'label' column X_train = train.drop(l..

import numpy as np import pandas as pd from keras.models import Sequential from keras import layers from keras.layers import BatchNormalization from keras.layers import Convolution2D, MaxPooling2D from keras.layers.core import Reshape, Dense, Flatten, Dropout from sklearn.model_selection import train_test_split df_train = pd.read_csv('/content/drive/MyDrive/military/mnist/train.csv') target = df..