To build a CNN based model which can accurately detect melanoma. Melanoma is a type of cancer that can be deadly if not detected early. It accounts for 75% of skin cancer deaths. A solution that can evaluate images and alert dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.

• General Info
• Technologies Used
• Conclusions
• Acknowledgements

• The project is built using tensorflow CNN
• The Project dataset include 9 types of different skin diseases. CNN Model is used to detect Melanoma

• We built 3 Different Model
• First Model was a overfit with Training Accuracy of 0.95 and validation of around 0.55
• We fixed this Model overfit, we added additional neural network and dropout layers, which handled overfitting.
• Since the data was skewed for number samples to train on was limited and hence we agumented data and achived a accuracy: 0.8027 and val_accuracy: 0.7988

• Tensorflow - version 2.8.0

Created by [@yashyennam] - feel free to contact me!