Closed abhisheks008 closed 4 weeks ago
hi abhisekh Full name: Yuvika Singh git hub profile link:https://github.com/Yuvika-14/Yuvikademo.git approch: ensemble methods, gradient boosting, neural networks. Take care of the missing data if there are any categorical values then will use one hot encoder or label encoder depending upon the issue.
One issue at a time @Yuvika-14
Raj Rawariya https://github.com/Raj100 All Regression models JWoC
Hi @Raj100 follow the issue template and put your comments accordingly. Your approach should be to the point and brief, which ensures your determination for this project, if you comment out like this, no one will assign you an issue in a PAN India open source event of highest quality.
Follow this,
In your approach mention the specific models you want to work on, how that will help the project, how the models will justify your project with the given dataset, how to measure the best fitted model for this project, all these things should be mentioned. I hope you understand.
@Raj100
Full name :Raj Rawariya GitHub Profile Link :https://github.com/Raj100 Participant ID (If not, then put NA) :NA Approach for this Project : Regression and classification models to try to find health score based on sleep patterns and lifestyle(make a supervised model to identify the lifestyle and sleep disorders) What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) JWoC
Issue assigned to you @Raj100
Nishtha Pabreja Nishtha1203 Linear Regresion, KNN, Decision Tree, Random Forest JWoC
This issue is already assigned to someone.
Hi @abhisheks008 👋🏻, I want to contribute to this issue, please assign it to me under SSOC.. 🥹
Full name : S G V Kamalakar
GitHub Profile Link : Sgvkamalakar
Participant ID (If not, then put NA): NA
Approach for this Project: Performing EDA on the dataset, creating visualization plots, and classifying the data based on the Sleep Disorder category using various ML classifiers (like RF, DT, Logistic, etc..) and Feedforward NN models. Developing an interactive UI for predicting outcomes based on user input.
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.): SSOC
Full name : Tanishka Bhalla GitHub Profile Link: https://github.com/Tanishka023 Participant ID (If not, then put NA) :NA Approach for this Project : EDA, KNN, Linear Regression What is your participant role? SSoC'24
Hi @abhisheks008 👋🏻, I want to contribute to this issue, please assign it to me under SSOC.. 🥹
Full name : S G V Kamalakar
GitHub Profile Link : Sgvkamalakar
Participant ID (If not, then put NA): NA
Approach for this Project: Performing EDA on the dataset, creating visualization plots, and classifying the data based on the Sleep Disorder category using various ML classifiers (like RF, DT, Logistic, etc..) and Feedforward NN models. Developing an interactive UI for predicting outcomes based on user input.
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.): SSOC
Implement 5-6 models for this project.
Assigned @Sgvkamalakar
Hi @abhisheks008 👋🏻, I want to contribute to this issue, please assign it to me under SSOC.. 🥹 Full name : S G V Kamalakar GitHub Profile Link : Sgvkamalakar Participant ID (If not, then put NA): NA Approach for this Project: Performing EDA on the dataset, creating visualization plots, and classifying the data based on the Sleep Disorder category using various ML classifiers (like RF, DT, Logistic, etc..) and Feedforward NN models. Developing an interactive UI for predicting outcomes based on user input. What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.): SSOC
Implement 5-6 models for this project.
Assigned @Sgvkamalakar
Noted.. Thanks for assigning ...
Hello @Sgvkamalakar! Your issue #512 has been closed. Thank you for your contribution!
ML-Crate Repository (Proposing new issue)
:red_circle: Project Title : Sleep Health and Lifestyle Dataset Analysis :red_circle: Aim : The aim of this project is to analyze the given dataset properly using machine learning methods. :red_circle: Dataset : https://www.kaggle.com/datasets/uom190346a/sleep-health-and-lifestyle-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.
📍 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 :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎