Simple Handwritten Character Recognition Classifier

# Introduction

In this project, you will learn how to build a simple handwritten character recognition classifier using the DIGITS dataset provided by the scikit-learn library. Handwritten character recognition is a classic problem in machine learning, and this project will guide you through the process of creating a classifier that can accurately predict the digit represented in a handwritten character image.

## 🎯 Tasks

In this project, you will learn:

- How to load the DIGITS dataset and split it into training and testing sets
- How to create and train a Support Vector Machine (SVM) classifier on the training data
- How to implement a function to classify a single handwritten character image
- How to test the classifier with a sample handwritten character image

## 🏆 Achievements

After completing this project, you will be able to:

- Load and preprocess a dataset for machine learning tasks
- Create and train an SVM classifier using scikit-learn
- Implement a prediction function to classify new samples
- Understand the basics of handwritten character recognition using machine learning techniques