About This Hackathon

<h3>Welcome to Week 23 of the Weekly MachineHack Hackathon Series!</h3><p>This week brings an exciting new challenge in the domain of computer vision: classifying images based on their respective emotions. This task is designed to test your skills in deep learning, computer vision, and model optimization while tackling a highly impactful problem. We look forward to seeing the innovative solutions you bring to the table!</p><h3><strong>Challenge Details</strong></h3><p>Your task is to develop a robust image classification model capable of predicting the emotion depicted in an image. The training dataset contains labeled images along with their respective emotions, while the test dataset includes images for which predictions must be generated. Participants are encouraged to explore state-of-the-art computer vision techniques to achieve high accuracy.</p><h3><strong>Participation and Benefits</strong></h3><ul><li><strong>Intermediate Level:</strong> This hackathon is ideal for participants with a basic understanding of machine learning and deep learning techniques, especially convolutional neural networks (CNNs).</li><li><strong>Community Engagement:</strong> Join our dynamic community on Telegram to share ideas, ask questions, and collaborate with fellow participants.</li><li><strong>Certificates:</strong> Every participant will receive a certificate from MachineHack, and winners will earn a spot on the leaderboard.</li><li><strong>Live Walkthrough Session:</strong> Attend a live session on [Date and Time] to gain valuable insights and tips for approaching this challenge.</li></ul><h3><strong>Submission and Evaluation</strong></h3><ul><li><strong>Submission Format:</strong> Participants must submit their predictions in the format specified in submission.csv.</li><li><strong>Evaluation Metric:</strong> Submissions will be evaluated based on the <strong>Accuracy Score</strong>, measuring how well the model classifies images into the correct emotion categories.</li><li><strong>Leaderboard:</strong> Track your progress and aim for the top spot on the leaderboard.</li></ul><h3><strong>Data Description</strong></h3><p>The dataset for this hackathon includes:</p><ul><li><strong>train.csv:</strong> Contains image names and their respective emotions for training.</li><li><strong>test.csv:</strong> Contains the image names for which participants must predict the emotions.</li><li><strong>Images.zip:</strong> A zip file containing all the images required for training and testing.</li><li><strong>submission.csv:</strong> The format in which your predictions should be submitted.</li></ul><h3><strong>How to Crack This Challenge</strong></h3><p>To tackle this challenge successfully, follow these steps:</p><p><strong>Data Preprocessing:</strong></p><ul><li>Normalize image data for better model performance.</li><li>Perform data augmentation techniques such as rotation, flipping, and scaling to make the model more robust.</li></ul><p><strong>Model Development:</strong></p><ul><li>Use pre-trained models like ResNet, VGG, or EfficientNet, fine-tuning them for emotion classification.</li><li>Experiment with custom CNN architectures to see if they outperform pre-trained models.</li></ul><p><strong>Training and Optimization:</strong></p><ul><li>Employ techniques like learning rate scheduling, early stopping, and dropout regularization to avoid overfitting.</li><li>Utilize libraries like TensorFlow, PyTorch, or Keras for efficient model building.</li></ul><p><strong>Validation and Testing:</strong></p><ul><li>Ensure your model generalizes well by using k-fold cross-validation.</li><li>Generate predictions for the test dataset in the required format.</li></ul><p>For our subscribers, a <strong>starter notebook</strong> will be available to guide you through data preprocessing 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: 2025-01-30T17:18:00Z
• End Date: 2025-02-23T23:23:59Z
• Current Participants: 111

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

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Quick Summary

Emotions Prediction Hackathon is a intermediate level hackathon currently expired. It has 111 participants. Prizes include: Knowledge. The event runs from 2025-01-30T17:18:00Z to 2025-02-23T23:23:59Z.Registration is free and open to all skill levels.