Kaggle Competetion

As part of the course, students are required to participate in a Kaggle competition focused on classifying blueberry production levels using real-world agricultural data.

The objective of the competition is to:

• Predict the production class of blueberry crops. Low, medium, or high.
• Apply machine learning techniques learned in the course to a structured dataset.
• Experiment with data preprocessing, feature selection, and model tuning.
• Improve predictive performance based on leaderboard feedback.

Students must:

• Register on Kaggle and join the course competition once it is released.
• Build and submit valid prediction files according to the competition instructions.
• Actively iterate on their models to improve results.

Follow Kaggle’s code of conduct and academic integrity guidelines.

Participation in the Kaggle competition is mandatory and contributes to the overall course assessment. Further details, including deadlines and evaluation criteria, will be shared when the competition opens.