Image Classification using Convolutional Neural Networks (CNN)

This project demonstrates how to build an image classification model using a Convolutional Neural Network (CNN) with TensorFlow and Keras. It classifies images into categories based on features learned from the data.

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Project Files

• Image_classification.ipynb – Main Jupyter notebook with full code.
• requirements.txt – Python libraries used in the project.
• README.md – Project overview and setup instructions.

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What the Project Does

• Loads and processes image data using ImageDataGenerator.
• Builds a CNN with layers like Conv2D, MaxPooling2D, Dropout, and Dense.
• Trains the model and plots training vs. validation accuracy and loss.
• Tests the trained model on new images for prediction.

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Technologies Used

• Language: Python
• Libraries: TensorFlow, Keras, NumPy, Matplotlib
• Model Architecture: Convolutional Neural Network (CNN)

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🔧 Setup Instructions

Clone the Repository

git clone https://github.com/your-username/image-classification-cnn.git
cd image-classification-cnn