abhisheks008 / DL-Simplified

Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013
https://quine.sh/repo/abhisheks008-DL-Simplified-499023976
MIT License
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[Project Addition]: Plant Disease Prediction using DL #672

Open Seersha9802 opened 1 month ago

Seersha9802 commented 1 month ago

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Plant disease prediction
:red_circle: Aim :Plant Disease Prediction with Image Classification
:red_circle: Dataset :https://www.kaggle.com/datasets/abdallahalidev/plantvillage-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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Happy Contributing šŸš€

All the best. Enjoy your open source journey ahead. šŸ˜Ž

github-actions[bot] commented 1 month ago

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

Seersha9802 commented 1 month ago

@abhisheks008 can you please assign this to me under GSSOC 24

abhisheks008 commented 1 month ago

What are the CNN architectures you are planning to implement for this project? Can you be specific on this as you need to implement 2-3 architecturs/models for this dataset.

Seersha9802 commented 1 month ago

Will be using pretrained and custom cnn models for classification (pre-trained: resent50, vgg16, inception) @abhisheks008

abhisheks008 commented 1 month ago

Cool go ahead @Seersha9802

Seersha9802 commented 1 month ago

May I know what contributions are marked as level 3? @abhisheks008

abhisheks008 commented 1 month ago

If you can implement 4-5 models for this project, it'll be considered as level 3. Based on the quality of the contribution, labels are assigned here in this repo.