Closed abhisheks008 closed 5 months ago
@abhisheks008 can you assign me this task? Full name : Pawas Pandey GitHub Profile Link : github.com/pawaspy Participant ID (If not, then put NA) : NA Approach for this Project : I will use different models such as random forest, gradient boosting or some sequential model to predict the data and matplotlib and seaborn for analysis. What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) : IWoC
Issue assigned to you @pawaspy
@abhisheks008 Can you please me assign this issue? Full name : Ghousiya Begum GitHub Profile Link : github.com/ghousiya47 Participant ID (If not, then put NA) : NA Approach for this Project : I will use different supervised machine leaening algorithms such as randomforest, svm to predict the data and matplotlib and seaborn for analysis, and we can check accuracy using skleanr.metrics package. in order to increase accuracy i will do hyperparameter tuning. What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) : JWoC
@ghousiya47 this issue has been already assigned.
thank you sir for assigning me this oppurtunity, i have done internships on AI ML and created machine learning models, i usually use google collab notebook, but i dont know how to contribute to github, the first step i have to do here is click new issue or pull requests? I joined jwoc peogram late so i didnt attend the class on github contribution, so i apologise for disturbing you.
thank you sir for assigning me this oppurtunity, i have done internships on AI ML and created machine learning models, i usually use google collab notebook, but i dont know how to contribute to github, the first step i have to do here is click new issue or pull requests? I joined jwoc peogram late so i didnt attend the class on github contribution, so i apologise for disturbing you.
Issue is already created by me and assigned to you for working. Firstly, you fork this repo in your local system, make the project, upload the files according to the project structure mentioned in the Discord server (I have also pinned the message). Then push your code by making a pull request. You can check out verious YouTube videos for the same to have an idea about it.
thank you sir for assigning me this oppurtunity, i have done internships on AI ML and created machine learning models, i usually use google collab notebook, but i dont know how to contribute to github, the first step i have to do here is click new issue or pull requests? I joined jwoc peogram late so i didnt attend the class on github contribution, so i apologise for disturbing you.
This issue is not assigned to you. Issue #519 is assigned to you, not this one. @ghousiya47
Check the labels first and the assignees section.
thank you sir for assigning me this oppurtunity, i have done internships on AI ML and created machine learning models, i usually use google collab notebook, but i dont know how to contribute to github, the first step i have to do here is click new issue or pull requests? I joined jwoc peogram late so i didnt attend the class on github contribution, so i apologise for disturbing you.
This issue is not assigned to you. Issue #519 is assigned to you, not this one. @ghousiya47
okay sir
ML-Crate Repository (Proposing new issue)
:red_circle: Project Title : Crop Production Data Analysis :red_circle: Aim : The aim of this project is to analyze the dataset using machine learning methods. :red_circle: Dataset : https://www.kaggle.com/datasets/zsinghrahulk/crop-production-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.
π 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 π
All the best. Enjoy your open source journey ahead. π