Loading the data

In this section, we will start building and training our convolutional neural network:

1. We will start by importing the necessary libraries, including pandas, numpy, and matplotlib:

import warnings
warnings.filterwarnings("ignore")
import libraries 
import pickle
#Import Pandas for data manipulation using dataframes
import pandas as pd 
#Importing Numpy for data statistical analysis 
import numpy as np  
#Importing matplotlib for data visualisation
import matplotlib.pyplot as plt
import random

2. Next, we import three pickle files – the test, training, and validation datasets:

with open("./traffic-signs-data/train.p", mode='rb') as training_data:
    train = pickle.load(training_data)
with open("./traffic-signs-data/valid.p", mode='rb') as validation_data:
    valid = pickle.load(validation_data)
with open("./traffic-signs-data/test.p", mode='rb') as testing_data:
    test = pickle.load(testing_data...