CIFAR-10 – modeling, building, and training

This example shows how to make a CNN for classifying images in the CIFAR-10 dataset. We'll be using a simple convolution neural network implementation of a couple of convolutions and fully connected layers.

Even though the network architecture is very simple, you will see how well it performs when trying to detect objects in the CIFAR-10 images.

So, let's start off this implementation.

Used packages

We import all the required packages for this implementation:

%matplotlib inline
%config InlineBackend.figure_format = 'retina'

from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import tarfile
import numpy as np
import random...