About This Hackathon

<h2>Data Engineering Summit - India's first &amp; only conference dedicated to the emerging field of Data Engineering.</h2><p><strong>Data Engineering Summit 2025</strong> The data landscape is rapidly evolving, driven by innovations in DataOps, real-time pipelines, and LLMOps. Concepts like data mesh, semantic layers, and generative AI are transforming chaotic data into trusted, high-value assets. As enterprises build future-ready platforms, the focus is shifting toward quality, scalability, and intelligent automation across the entire data lifecycle.</p><p>🚀 <strong>We bring you an exciting new challenge in machine learning: Predicting E-commerce Product Ratings</strong>! This challenge is designed to drive innovation in building intelligent, customer-centric e-commerce platforms a critical component of today’s digital shopping experience.</p><h3><strong>Challenge Details</strong></h3><p>Develop a machine learning model that predicts <strong>product ratings</strong> based on various features from e-commerce product data. Accurate product rating predictions can significantly enhance the <strong>personalization of recommendations</strong>, improve <strong>customer satisfaction</strong>, and optimize <strong>inventory and marketing strategies</strong> across e-commerce platfo</p><h3>Participation and Benefits</h3><ul><li>Intermediate Level: This hackathon is ideal for participants with a basic understanding of machine learning and deep learning techniques.</li><li>Community Engagement: Join our dynamic community on <a target="_blank" rel="noopener noreferrer" href="https://t.me/joinchat/NJLxnlWiz9lFnEJU20Sccw">Telegram</a> to share ideas, ask questions, and collaborate with fellow participants.</li><li>Certificates: Every participant will receive a certificate from MachineHack, and winners will earn a spot on the leaderboard.</li></ul><h3>Submission and Evaluation</h3><ul><li>Submission Format: Participants must submit their predictions in the format specified in submission.csv and the notebook.</li><li>Evaluation Metric: Submissions will be evaluated based on the RMSE , measuring how well the model predict product rating.</li><li>Leaderboard: Track your progress and aim for the top spot on the leaderboard.</li></ul><h3>Data Description</h3><p>The dataset for this hackathon includes:</p><ul><li>train.csv: Contains E-commerce data.</li><li>test.csv: Contains data for testing.</li><li>submission.csv: The format in which your predictions should be submitted.</li></ul><h3>How to Crack This Challenge</h3><p>To tackle this challenge successfully, follow these steps:</p><p><strong>Data Pre-processing</strong></p><ul><li>Handle Missing Values: Identify and impute or remove missing values.</li><li>Remove the unwanted columns.</li><li>Perform feature engineering.</li></ul><p><strong>Model Development</strong></p><ul><li>Use machine learning models like Random Forest and XGBoost for Predicting product rating.</li></ul><p><strong>Training and Optimization</strong></p><ul><li>Apply Grid Search CV for hyperparameter tuning.</li><li>Train model using user travel data.</li></ul><p><strong>Validation and Testing</strong></p><ul><li>Ensure the model generalizes well to unseen data.</li><li>Generate predictions for the test dataset in the required format for submission.</li></ul><p>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.</p><h3><strong>Getting Started</strong></h3><ol><li><strong>Register Now:</strong> Make sure to register for the hackathon to stay updated.</li><li><strong>Download the Dataset:</strong> Access the dataset from the MachineHack platform and start working.</li><li><strong>Join the Community:</strong> Interact with fellow participants and mentors via our Telegram group for discussions and support.</li></ol><h3><strong>Support and Resources</strong></h3><p>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.</p><h3><strong>Happy Hacking and Growing! 🚀</strong></h3>

Key Information

• Category: Hackathon
• Difficulty Level: Intermediate
• Status: Expired
• Start Date: 2025-05-14T14:28:00Z
• End Date: 2025-06-13T23:00:00Z
• Current Participants: 73

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>RMSE</p>

Quick Summary

E-commerce Product Rating Prediction is a intermediate level hackathon currently expired. It has 73 participants. Prizes include: Knowledge. The event runs from 2025-05-14T14:28:00Z to 2025-06-13T23:00:00Z.Registration is free and open to all skill levels.