Sure! Here's a solid list of competition rules tailored for an MNIST dataset-based machine learning competition. These balance fairness, creativity, and technical challenge—perfect for students or general participants:

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### 🧠 *MNIST Digit Recognition Competition Rules*

#### 📅 General Rules
1. *Eligibility*: Open to individuals or teams of up to 3 members.
2. *Registration Deadline*: 30 Apr 2025
3. *Submission Deadline*: 30 Apr 2025
4. *Team Naming*: Keep it clean, fun, and unique.
5. *One Entry per Team*: Only the final submission will be considered.

#### 📁 Dataset Rules
1. *Dataset*: Only the official MNIST dataset is allowed. You may use train/test splits as provided.
2. *No External Datasets*: External data for training is not permitted unless otherwise specified.

#### 🛠 Model and Code Rules
1. *Allowed Tools*: Any programming language or library (Python + TensorFlow, Keras, PyTorch, Scikit-learn, etc.) is allowed.
2. *Code Submission*: You must submit your full code along with your final predictions.
3. *Reproducibility*: Your code must be well-documented and reproducible.
4. *No Pretrained Models*: Models trained on external datasets (e.g., ImageNet) are not allowed.

#### 📊 Evaluation Criteria
1. *Accuracy*: Submissions will be ranked based on test set classification accuracy.
2. *Tie-Breaker*: In case of a tie, the most efficient model (e.g., fewer parameters, faster inference) may be chosen.
3. *Plagiarism*: Strictly prohibited. Copied code will lead to disqualification.

#### 🏆 Winning & Prizes
1. *Top Performers*: Prizes will be awarded to the top 3 teams.
2. *Judges' Choice*: A special mention may be given for creative approach, clean code, or innovative visualization.

#### 💬 Communication
1. *Doubts & Clarifications*: Post questions in the official competition forum/group.
2. *Mentorship*: Basic ML guidance will be available to beginners on request.

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