🧠 Handwritten Digit Recognition

This project is a basic implementation of a handwritten digit recognizer using the popular MNIST dataset. It classifies digits (0-9) based on grayscale image pixel data.

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📌 Description

The project uses a simple neural network / machine learning model to classify handwritten digits. It's a great starting point for learning computer vision and digit classification.

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🗂️ File Included

• AI_Project.ipynb: Jupyter notebook containing the entire code – data loading, model training, evaluation, and prediction.

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📊 Dataset Used

• MNIST – A dataset of 70,000 28x28 grayscale images of handwritten digits (0 to 9)
• Automatically loaded using tensorflow.keras.datasets or sklearn.datasets

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🚀 How to Run

1. Clone the repository:

   git clone https://github.com/YourOpen the notebook in Jupyter:
   

2.Open the notebook in Jupyter: jupyter notebook AI_Project.ipynb

3.Run all cells and follow the steps in the notebook.Username/Digit_Recognition.git cd Digit_Recognition