🫁 Pneumonia Detection from Chest X-Rays

This project implements a deep learning model to detect Pneumonia from chest X-ray images. It uses Convolutional Neural Networks (CNNs) for image classification and is trained on the Kaggle Chest X-Ray Pneumonia dataset.

---

🚀 Project Overview

• Goal: Classify X-ray images as Normal or Pneumonia.
• Dataset: 5,863 chest X-ray images (train, test, val) from Kaggle.
• Model: CNN built using TensorFlow/Keras.
• Metrics: Accuracy, Precision, Recall, F1-score.

---

🧠 Key Features

• Preprocessing and data augmentation using ImageDataGenerator.
• CNN architecture optimized for binary classification.
• Evaluation on unseen X-ray images.
• Trained model can be reused for inference or deployment.

---

📁 Dataset

The dataset can be downloaded from Kaggle:
👉 Chest X-Ray Pneumonia Dataset

🏃‍♂️ How to Run

Clone the repo:

git clone https://github.com/your-username/Pneumonia-Detection-Model.git cd Pneumonia-Detection-Model

Open the notebook:

jupyter notebook Pneumonia_Detection_Model.ipynb

or run it in Google Colab.