James Webb Telescope Images Analysis

[abhisheks008]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : James Webb Telescope Images Analysis
:red_circle: Aim : Analyze the recent images from the James Webb Telescope.
:red_circle: Dataset : https://www.kaggle.com/datasets/goelyash/james-webb-telescope-images-original-size/code
: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. 😎

[Rohith2202]

Madineni Rohith https://github.com/Rohith2202 20bcs081@iiitdwd.ac.in Will try various ML models and pick the right and most accurate one for James Webb Space Telescope Image analysis SSOC participant

[abhisheks008]

We'll start the journey after completing those formalities. Till then, stay tuned with Deep Learning Simplified.

Thanks and regards.

[LahariBoni]

Assigned it to you @Rohith2202. Happy Contribution!

[abhisheks008]

@Rohith2202 updates please.

[Rohith2202]

Almost done sir. Will submit in 2 days time

[abhisheks008]

Cool, thanks for the update @Rohith2202