Skin Cancer Classification using NasNet and ShuffleNet

• Tech Stack: Python, Tensorflow
• Github URL: Project Link

Developed and optimized deep learning models (Custom CNN, NasNet, ShuffleNet) for multi-class skin cancer classification using the HAM10000 dataset. Improved model accuracy and stability through batch normalization, dropout layers, and Adamax optimizer. Achieved highest classification accuracy with NasNet, while ShuffleNet enhanced computational efficiency using grouped convolutions and channel shuffling.

I am sorry this's research project and I am not allowed to share the code. Soon it'll publically available.