About This Hackathon

<p>Welcome<strong> to Week 14 of the Weekly MachineHack Hackathon Series!</strong></p><p>This week’s challenge focuses on developing a predictive model for food demand forecasting. Accurate forecasting is crucial for food supply chain management, allowing businesses to minimize waste and optimize inventory.</p><h3>About the Dataset</h3><p>The dataset consists of historical food demand data from various facilities, regions, and categories. You’ll analyze patterns and trends to predict future demand for food items, helping businesses make informed decisions.</p><p><strong>Dataset Description:</strong></p><ul><li><strong>Train.csv:</strong> Contains historical data with features like food items, demand quantity, and additional contextual information (e.g., promotions types).</li><li><strong>Test.csv:</strong> The dataset for which you will generate predictions.</li><li><strong>Submission.csv:</strong> The format for submitting your predictions.</li></ul><h3>Participation and Benefits:</h3><ul><li><strong>Skill Level:</strong> This challenge is designed for participants with experience in time series analysis, machine learning, and data preprocessing.</li><li><strong>Community Engagement:</strong> Join our Telegram group to connect with other participants, ask questions, and share insights.</li><li><strong>Recognition:</strong> All participants will receive a MachineHack certificate, and top performers will be highlighted on the leaderboard.</li><li><strong>Live Walkthrough:</strong> A live session will be held on [insert date] to guide you through the challenge and provide expert tips.</li></ul><h3>Submission and Evaluation:</h3><ul><li><strong>Submission Format:</strong> Submit your predictions in the provided Submission.csv file.</li><li><strong>Evaluation Metric:</strong> Submissions will be evaluated based on the <strong>Root Mean Squared Error (RMSE)</strong>.</li><li><strong>Leaderboard:</strong> Track your performance and strive to reach the top!</li></ul><h3>How to Approach the Challenge:</h3><ol><li><strong>Data Preprocessing:</strong> Clean and prepare the dataset for analysis, handling missing values and formatting issues.</li><li><strong>Feature Engineering:</strong> Create meaningful features that capture trends and seasonality (e.g., day of the week, month, promotions).</li><li><strong>Modeling Techniques:</strong> Experiment with models such as ARIMA, LSTM, Random Forest, or Gradient Boosting for time series forecasting.</li><li><strong>Validation and Tuning:</strong> Use cross-validation techniques and hyperparameter tuning to enhance model performance.</li></ol><p>A starter notebook will be available to guide you through the initial data preprocessing steps and basic model building.</p><h3>Getting Started:</h3><ul><li><strong>Register Now:</strong> Ensure you're registered to participate and receive updates.</li><li><strong>Download the Dataset:</strong> Access the dataset from the MachineHack platform and start building your solution.</li><li><strong>Join the Community:</strong> Connect with other participants via our Telegram group for tips, resources, and collaboration.</li></ul><h3>Support and Resources:</h3><p>For any questions, reach out to our support team at support@machinehack.com.&nbsp;</p><p>We’re excited to see your innovative solutions!</p>

Key Information

• Category: Hackathon
• Difficulty Level: Intermediate
• Status: Expired
• Start Date: 2024-10-31T21:30:00Z
• End Date: 2024-12-01T23:23:59Z
• Current Participants: 311

Prizes and Awards

Knowledge

Rules and Guidelines

<ul><li>The participants are required to provide the code for the work done.</li><li>The output of the code should match the submission file with the "Best Score" achieved by the participant.</li></ul>

Evaluation Criteria

<p>The evaluation will be performed over the <strong>Root Mean Squared Error (RMSE) </strong>metric between the submitted file and the ground truth.</p>

Quick Summary

Food Orders Forecasting is a intermediate level hackathon currently expired. It has 311 participants. Prizes include: Knowledge. The event runs from 2024-10-31T21:30:00Z to 2024-12-01T23:23:59Z.Registration is free and open to all skill levels.