Ethiopian Kale Leaf Image Analysis

[abhisheks008]

ML-Crate Repository (Proposing new issue)

:red_circle: Project Title : Ethiopian Kale Leaf Image Analysis :red_circle: Aim : Create a data analysis project to analyze the dataset provided to you. :red_circle: Dataset : https://www.kaggle.com/datasets/damtewmekash/ethiopiankale :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 :
• Participant ID (If not, then put NA) :
• Approach for this Project :
• What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.)

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Happy Contributing 🚀

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

[CoderOMaster]

Hi @abhisheks008 Full name : Keshav Arora GitHub Profile Link : https://github.com/CoderOMaster Participant ID (If not, then put NA) : Role: JWOC 2024 Mentee Approach for this Project: Various Deep learning techniques can be implemented using CNN,RNN and architectures like VGG,Resnet, inception for transfer learning. Data augmentation will be implemented if needed. Regards

[akanksha-2002]

Hi, @abhisheks008 ! I would like to take up this issue. Full name : Akanksha Bhimte GitHub Profile Link: https://github.com/akanksha-2002 Participant ID (If not, then put NA) : Approach for this Project:

1. EDA
2. Data preprocessing for analysis
3. Employing models such as CNN, GoogLeNet, Transfer Learning Models and Ensemble models to compare their performance and find the best fit.
4. Evaluation Metrics
5. Fine-tuning and Optimization with different architectures, hyperparameters, and regularization techniques.

What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) JWOC

[abhisheks008]

@akanksha-2002 and @CoderOMaster wait for the program to start officially. Once it is done, issues will be assigned to you accordingly.

[CoderOMaster]

Hi @abhisheks008 Full name : Keshav Arora GitHub Profile Link : https://github.com/CoderOMaster Participant ID (If not, then put NA) : Role: JWOC 2024 Mentee Approach for this Project: Various Deep learning techniques can be implemented using CNN,RNN and architectures like VGG,Resnet, inception for transfer learning. Data augmentation will be implemented if needed. Regards

[abhisheks008]

Issue assigned to you @akanksha-2002

[abhisheks008]

Hey @abhisheks008 Sir, please assign this issue to me under SSOC'24, I really want to work on this.

One issue at a time. Please do not spam.

[Tanishka023]

Heyy @abhisheks008 Full name : Tanishka Bhalla GitHub Profile Link : https://github.com/Tanishka023 Participant ID (If not, then put NA) : NA Role: SSoC Season 3 Approach for this Project: After processing the images, various ML models can be used such as SVM, KNN, LR, Random forests

[abhisheks008]

Heyy @abhisheks008 Full name : Tanishka Bhalla GitHub Profile Link : https://github.com/Tanishka023 Participant ID (If not, then put NA) : NA Role: SSoC Season 3 Approach for this Project: After processing the images, various ML models can be used such as SVM, KNN, LR, Random forests

One issue at a time.

[tanuj437]

@abhisheks008 The dataset link provided in this issue is not available as page can't be found showing, If there is any other link for it do provide i am up for working over it

Full name : Tanuj Saxena GitHub Profile Link : https://github.com/tanuj437 Participant ID (If not, then put NA) : NA Approach for this Project : EDA firstly then starting with Basic Algorithm like Logistic regression, SVM, K-NN ,Random Forest, Gradient boosting, then can go with Neural Networks like CNN What is your participant role? SSOC'24 season 3

[abhisheks008]

Implement 6-7 models for this project.

Assigned @tanuj437