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FIDE Chess Ranking Analysis #271
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@abhisheks008 What exactly we need to predict here can you explain this once!!!! is it just about drawing inferences and bringing out conclusions from different perspectives or predicting about certain aspect |
Yeah, this is a Data Analysis and visualization project, where you need to analyze different parameters and provide a bunch of conclusions at the end of the project. You can check other data analysis projects of ML-Crate for more clarification on how the things should be presented. And if you wanna work on specifically on a prediction/classification model oriented project, then you can check other issues. There are lots of issues on this. |
Full name : NIRVIK GHOSH |
@GundaSudarrshan are you willing to contribute in this issue, otherwise I'll assign this to @Nirvik07 |
@abhisheks008 could you hold this project for me if @GundaSudarrshan does want to work in it. Meanwhile I can work on another issue and finish it up and later on take this issue up. is ok for you? @abhisheks008 |
Yeah sure @Nirvik07 |
yes @abhisheks008 I wanted to Work on this Issue |
Full name : Gunda Sudarrshan |
Issue assigned to you @GundaSudarrshan |
Updates please @GundaSudarrshan |
@abhisheks008 sorry for the Delay , I was having My end semester Exams so I was Unable to Contribute much, I will try to update by weekend , If that's not ok for you can reassign to someone. |
Don't worry. Concentrate in your end sem exams, you can complete it later on @GundaSudarrshan |
Weekend is coming up! How's all going with your exams? @GundaSudarrshan |
@abhisheks008 I think you can assign this to someone else, I have exams till 8th august ,I will be free from that day |
As you wish. All the best for your exams @GundaSudarrshan |
@abhisheks008 can you assign me this? |
Issue assigned to you @Nirvik07 |
ML-Crate Repository (Proposing new issue)
🔴 Project Title : FIDE Chess Ranking Analysis
🔴 Aim : Analyze the dataset with different parameters.
🔴 Dataset : https://www.kaggle.com/datasets/surajjha101/fide-chess-rankings-updated
🔴 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. 😎
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