Skin Disease Classification using Deep Learning Models

[pacificrm]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Skin Disease Classification using Deep Learning Models
:red_circle: Aim : To build a model to classify various Skin diseases
:red_circle: Dataset : https://www.kaggle.com/datasets/pacificrm/skindiseasedataset/data
:red_circle: Approach : First Analyze the dataset by checking image quality, class distributions, and visualization of sample images. Then I train various models to enhance the classification accuracy, I propose building and comparing various models to select the best one. The models to be used include: VGG /(Custom model) ResNet SEResNet EfficientNet Vision Transformer (ViT)

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📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

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:white_check_mark: To be Mentioned while taking the issue :

• Full name : Prashant Kumar Mishra
• GitHub Profile Link : https://github.com/pacificrm
• Email ID : ur.pm.ru@gmail.com
• Participant ID (if applicable):
• Approach for this Project : Mentioned above.
• What is your participant role? GSSOC-EXT and Hacktoberfest

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[github-actions[bot]]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[abhisheks008]

Assigning this issue to you @pacificrm. You can start working on it.