A modular deep learning framework for training and evaluating image classification models on datasets like CIFAR-10 and MNIST. Supports configurable CNN architectures, automated training, and performance visualization using Python and TensorFlow.
This project provides a modular deep learning framework for training and evaluating image classification models.
- Modular CNN architecture
- CIFAR-10 dataset support
- Training and evaluation scripts
- Accuracy visualization
datasets/ – dataset storage
models/ – deep learning model architectures
training/ – training scripts
utils/ – helper functions
notebook/ – experimentation notebooks
Python
TensorFlow
Keras
Google Colab
- Computer vision experiments
- Deep learning research
- Educational AI projects
pip install -r requirements.txt
python training/train.py
This project currently supports the CIFAR-10 dataset.
The CNN model achieves good classification accuracy on CIFAR-10.
- Add ResNet architecture
- Add MobileNet
- Add data augmentation
- Add ResNet and MobileNet models
- Support custom datasets
- Add data augmentation pipeline
MIT License