Facial Skin Diseases Classification using DL

[abhisheks008]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Facial Skin Diseases Classification using DL
:red_circle: Aim : The aim of this project is to classify the dataset using deep learning methods.
:red_circle: Dataset : https://www.kaggle.com/datasets/osmankagankurnaz/facial-skin-diseases-dataset
:red_circle: Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.

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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 :
• GitHub Profile Link :
• Email ID :
• Participant ID (if applicable):
• Approach for this Project :
• What is your participant role? (Mention the Open Source program)

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Happy Contributing 🚀

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

[byte-wanderer]

Full Name : Shaashwat Dagar GitHub Profile Link : https://github.com/byte-wanderer Email ID : dagarshaashwat@gmail.com Participant ID (if applicable): Approach for this Project : First approach to Facial Diseases identification using deep learning is to use recurrent neural networks (RNNs), capable of modeling sequential dependencies in text data. (RNNs can be further improved by incorporating long short-term memory (LSTM) or gated recurrent unit (GRU) cells). Another approach is to use convolutional neural networks (CNNs), which are useful in identifying local patterns in text data What is your participant role? (Mention the Open Source program): SWOC(S4) Contributor

[abhisheks008]

Assigned @byte-wanderer

[aditya-bhaumik]

Full name : Aditya Bhaumik GitHub Profile Link : https://github.com/aditya-bhaumik Email id : adi.b98120@gmail.com Approach for this Project : In the initial phase of Facial Diseases identification using deep learning,

It will basically involve utilizing recurrent neural networks (RNNs), which excel in modeling sequential dependencies, making them suitable for analyzing sequential data like text. We can enhance RNNs by incorporating long short-term memory (LSTM) or gated recurrent unit (GRU) cells, which help capture long-range dependencies and mitigate the vanishing gradient problem.

Then i will try to leverage convolutional neural networks (CNNs), which are adept at identifying local patterns in data. By applying these approaches, we aim to develop models capable of effectively classifying facial skin diseases based on image data, with the potential for further optimization and improvement through experimentation and fine-tuning of model architectures and parameters.

What is your participant role? (Mention the Open Source program) : GSSOC 2024 Contributor

@abhisheks008 Please assign me this issue under GSSOC'24 label

[abhisheks008]

Cool, your approach looks good to me. Issue assigned to you @aditya-bhaumik