Classifying Handwritten Digits with TensorFlow

Handwritten digit classification is a classic problem in machine learning and computer vision. It involves identifying the digit (0–9) from an image of a handwritten digit. In this blog post, we will walk you through a project that uses TensorFlow to classify handwritten digits from the popular MNIST dataset. We will provide a step-by-step implementation and explanation, ensuring that even those with no prior knowledge can follow along.

Table of Contents

• Introduction
• What is Handwritten Digit Classification?
• The MNIST Dataset
• Project Implementation

Step 1: Import Required Libraries

Step 2: Load the MNIST Dataset

Step 3: Display Sample Images

Step 4: Normalize the Images

Step 5: Build and Compile the Model

Step 6: Train the Model

Step 7: Evaluate the Model

Step 8: Create an Interactive GUI

• Conclusion
• FAQs

Introduction

In this project, we’ll build a neural network capable of identifying handwritten digits using TensorFlow. We’ll use the MNIST…