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ElectricRangeEstimationModel

Expired
Start: March 27, 2025Ends: April 23, 2025
Participants
103
Time Left
Ended
Subs/day
9
Challenge Overview

Welcome to Week 27 of the Weekly MachineHack Hackathon Series!

This week brings an exciting new challenge in the domain of machine learning: Electric Range Estimation Model predicts how far an electric vehicle (EV) can travel on a full charge,Electric vehicle (EV) buyers and manufacturers need an accurate way to estimate the expected electric range of an EV based on its specifications.

Challenge Details

Your task is to develop a machine learning model that predicts the expected electric range based on given data.

Participation and Benefits

  • Intermediate Level: This hackathon is ideal for participants with a basic understanding of machine learning and deep learning techniques.
  • Community Engagement: Join our dynamic community on Telegram to share ideas, ask questions, and collaborate with fellow participants.
  • Certificates: Every participant will receive a certificate from MachineHack, and winners will earn a spot on the leaderboard.

Submission and Evaluation

  • Submission Format: Participants must submit their predictions in the format specified in submission.csv.
  • Evaluation Metric: Submissions will be evaluated based on how accurately the model predicts the electric range, using Root Mean Squared Error (RMSE) as the evaluation metric.
  • Leaderboard: Track your progress and aim for the top spot on the leaderboard.

Data Description

The dataset for this hackathon includes:

  • train.csv: Contains electrics vehicle population data.
  • test.csv: Contains data for testing.
  • submission.csv: The format in which your predictions should be submitted.

How to Crack This Challenge

To tackle this challenge successfully, follow these steps:

Data Pre-processing

  • Handle Missing Values: Identify and impute or remove missing values.
  • Remove the unwanted columns.
  • Normalised the numerical features.
  • Encode categorical value.
  • Perform feature selection.

Model Development

  • Use machine learning models like Random Forest ,CatBoost,LightGBM and XGBoost for electric range prediction.

Training and Optimization

  • Apply Grid Search CV , RandomizedSearchCV for hyperparameter tuning.
  • Train model using electrics vehicle population data.

Validation and Testing

  • Ensure the model generalizes well to unseen data.
  • Generate predictions for the test dataset in the required format for submission.

For our subscribers, a starter notebook will be available to guide you through data pre-processing and basic model building. You can customize and enhance this framework to develop your solution further.

Getting Started

  1. Register Now: Make sure to register for the hackathon to stay updated.
  2. Download the Dataset: Access the dataset from the MachineHack platform and start working.
  3. Join the Community: Interact with fellow participants and mentors via our Telegram group for discussions and support.
  4. Submission guideline :You can submit up to 9 solutions per day. If you exceed this limit, please submit your solution on the next day.

Support and Resources

For any questions or assistance, please reach out to our support team at support@machinehack.com. Stay informed about the latest announcements by subscribing to our newsletter.

Happy Hacking and Growing! 🚀

Problem Statement

This challenge focuses on building advanced machine learning models to solve real-world problems. Participants will work with carefully curated datasets and compete to achieve the best performance metrics.

Target Column: Electric_Range
Metric: root_mean_squared_error
Level: Intermediate
Submissions: 9/day
Top Submissions

No leaderboard data available

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Electric Range Estimation Model

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    Electric Range Estimation Model | Hackathon Hackathon | MachineHack