🧠 CNN Image Classification.

CIFAR-10 Image Classification using PyTorch

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🚀 About

A Convolutional Neural Network (CNN) built with PyTorch to classify images from the CIFAR-10 dataset.

Data → Preprocessing → CNN → Training → Evaluation → Prediction

📊 Dataset

CIFAR-10 contains 60,000 color images across 10 classes:

✈️ Airplane · 🚗 Automobile · 🐦 Bird · 🐱 Cat · 🦌 Deer · 🐶 Dog · 🐸 Frog · 🐴 Horse · 🚢 Ship · 🚚 Truck

🧠 Model

Input Image
     ↓
Convolution
     ↓
Activation + Pooling
     ↓
Feature Extraction
     ↓
Fully Connected Layers
     ↓
10-Class Prediction

🎯 Results

Metric	Result
Dataset	CIFAR-10
Framework	PyTorch
Model	CNN
Test Accuracy	75.07%
Classes	10

🛠️ Tech Stack

Python · PyTorch · TorchVision · Matplotlib · Google Colab

▶️ Run

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

Open CNN.ipynb in Google Colab or Jupyter Notebook and run the cells.

📁 Project Structure

cnn-image-classification/
└── CNN.ipynb

👨‍💻 Author

Sumit Jha

⭐ If you found this project useful, consider starring the repository!

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Built with 🧠 PyTorch & ❤️ for Deep Learning

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