application_vnd.jupyter.stderr_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

train = pd.read_csv('/kaggle/input/Kannada-MNIST/train.csv')

test = pd.read_csv('/kaggle/input/Kannada-MNIST/test.csv')

images = train.iloc[:, 1:].values.reshape(train.shape[0], 28, 28).astype('float32') / 255.0
images = images.reshape(train.shape[0], 28, 28, 1)
images_test = test.iloc[:, 1:].values.reshape(test.shape[0], 28, 28).astype('float32') / 255.0
images_test = images_test.reshape(test.shape[0], 28, 28, 1)
label = train.iloc[:, 0].astype('int').values
ids_test = test.iloc[:, 0].values
plt.imshow(images[0].reshape(28, 28), cmap='gray')
plt.title(label[0])