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Used Car Price Prediction #653
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Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊 |
Full name :Mayuresh Dharwadkar @abhisheks008 Pls assign this issue to me. Regards |
Full name: Milan Prajapati GitHub Profile Link: GitHub_Profile Participant ID (If not, then put NA): NA Approach for this Project:
What is your participant role? : VSoC Sir, can You Please assign this project to me...? |
Full name : Vansh Gupta To predict used car prices using machine learning methods, we will follow a structured approach that includes data acquisition, exploratory data analysis (EDA), preprocessing, model building, and evaluation. Here's a step-by-step plan:
Preprocessing involves cleaning and transforming the raw data into a format suitable for modeling:
We'll build multiple models and compare their performance:
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.): VSOC |
Implement 6-7 models for this project/problem statement. |
Full name : Tanuj Saxena |
Assigned @tanuj437 |
ML-Crate Repository (Proposing new issue)
🔴 Project Title : Used Car Price Prediction
🔴 Aim : The aim is to predict the used car price using machine learning methods.
🔴 Dataset : https://www.kaggle.com/datasets/zeeshanlatif/used-car-price-prediction-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. 😎
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