Deep Learning and AI Superhero

Practical Exercises Chapter 5

Exercise 1: Implementing a Basic CNN for Image Classification

Task: Implement a simple CNN from scratch to classify images from the MNIST dataset. Train the model for a few epochs and evaluate its accuracy.

Solution:

import torch

import torch.nn as nn

import torch.optim as optim

from torchvision import datasets, transforms

from torch.utils.data import DataLoader

# Define the CNN model

class SimpleCNN(nn.Module):

def __init__(self):

super(SimpleCNN, self).__init__()

self.conv1 = nn.Conv2d(1, 32, kernel_size=3)

self.pool = nn.MaxPool2d(2, 2)

self.conv2 = nn.Conv2d(32, 64, kernel_size=3)

self.fc1 = nn.Linear(64 * 5 * 5, 128)

self.fc2 = nn.Linear(128, 10)

def forward(self, x):

x = self.pool(torch.relu(self.conv1(x)))

x ...