Closed aaradhyasinghgaur closed 4 weeks ago
Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊
One issue at a time.
Assigned @kyra-09
Hello @kyra-09! Your issue #696 has been closed. Thank you for your contribution!
Deep Learning Simplified Repository (Proposing new issue)
:red_circle: Project Title : Natural Diamonds Image Classification on the basis of shape. :red_circle: Aim : Classification of different types of natural diamonds on the basis of shapes like round, cushion, radiant, emerald, heart, oval, etc using dl modles and comparing their preformance using different matrices such as accuracy score , confusion matrix , plotting graphs and doing EDA analysis . :red_circle: Dataset : https://www.kaggle.com/datasets/harshitlakhani/natural-diamonds-prices-images/data :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.
📍 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.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
To classify different shapes of natural diamonds (e.g., round, cushion, radiant, emerald, heart, oval, etc.), we will employ five distinct deep learning network architectures:
These techniques will artificially expand the dataset and help prevent overfitting.
Model Performance Comparison: We will evaluate and compare the performance of each model using the following metrics and visualizations:
Exploratory Data Analysis (EDA): Before training the models, we will perform comprehensive exploratory data analysis (EDA) on the dataset to understand its structure. This will include:
README File: A README file will be created to document the entire process according to the READMe template.
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎