text_plain_output_1.png
import pandas as pd

import pandas as pd
import numpy as np
import tensorflow as tf
import keras
from keras.models import Sequential
from keras.layers import Dense, Activation, Dropout, Flatten, Conv2D, MaxPooling2D, AveragePooling2D
from keras.layers.normalization import BatchNormalization
from keras.callbacks import ReduceLROnPlateau
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import itertools
import seaborn as sns
X = pd.read_csv('../input/train.csv')
X_test_main = pd.read_csv('../input/test.csv')
y = X['label']
X = X.drop(['label'], axis=1)
X = X.values.reshape(-1, 28, 28, 1).astype('float32')
X_test_main = X_test_main.values.reshape(-1, 28, 28, 1).astype('float32')
y = y.values

X.shape