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Implementation of Resnet152 to achieve accuracy of 0.99 in the public leaderboard

Importing necessary libraries

%reload_ext autoreload
%autoreload 2
%matplotlib inline

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import seaborn as sns

from sklearn.model_selection import train_test_split
from fastai.vision import *
from fastai.metrics import error_rate

Variables initialization

SEED = 42
VALIDATION_PCT = 0.1
IMAGE_SIZE_64 = 64
IMAGE_SIZE_224 = 224
BATCH_SIZE_64 = 64
BATCH_SIZE_224 = 224
PATH = Path('../input')
TRAIN_PATH = PATH/'train'
TEST_FOLDER_PATH = "test/test"
SAMPLE_SUBMISSION_PATH = PATH/"sample_submission.csv"