You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
🔴 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.
📍 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.
🔴🟡 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.
✅ 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)
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
The text was updated successfully, but these errors were encountered:
Hi @abhisheks008, I would like to work on this issue as part of Social Winter of Code. Could you please assign it to me? Looking forward to contributing!
Approach for this Project: Implementing Vedanthangal Water Birds classification using a custom CNN, EfficientNet, ResNet50, and Vision Transformer (ViT), comparing their performance to identify the best model based on accuracy and evaluation metrics.
Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Vedanthangal Water Birds Classification using DL
🔴 Aim : The aim is to analyse the given dataset and build a deep learning model to understand the water birds.
🔴 Dataset : https://www.kaggle.com/datasets/solomonmelwin2002/vedanthangal-water-birds-dataset
🔴 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.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
The text was updated successfully, but these errors were encountered: