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Machine Learning and Artificial Intelligence
The capstone of camp translates students’ cleaned datasets into working predictive models and, ultimately, AI-enabled tools for smarter agriculture. Day 1 builds conceptual fluency—what ML is, where it shines, and where it can mislead—then dives into supervised vs. unsupervised methods, famous algorithms, the differences between machine learning and deep learning, what it takes to train an AI algorithm, and the ethical implications of deploying AI on the farm. Day 2 is fully hands-on: campers code simple models, advance to a neural-network stretch goal, and benchmark results against the heuristics they saw in earlier modules. A post-camp reflection, coupled with a graduation showcase, ensures each participant leaves with a runnable notebook and a clear path to continue learning after camp.
| When | Session | Key activities & learning goals |
|---|---|---|
| 7 July | Field Trip: Planted Detroit Vertical Farm |
• Observe advanced technologies used in a commercial vertical farm • Connect real growing systems to data collection, monitoring, and decision-making |
| Introduction to ML – Applications, Dos & Don’ts |
• Define ML vs. traditional programming • Highlight data-quality pitfalls: leakage, imbalance, and overfitting • Discuss the “right problem–right tool” mindset |
|
| Supervised vs. Unsupervised Learning |
• Introduce supervised and unsupervised learning basics and algorithms • Compare accuracy, interpretability, and data requirements |
|
| From ML to Deep Learning to AI – Plus Ethics |
• Walk through neural-network layers and transfer learning • Explore a case study: CNN for ripeness detection • Discuss bias, transparency, and the environmental cost of AI models |
|
| 8 July | ML-AI Coding Lab |
• Load the cleaned camp dataset into a notebook and split train/test data • Train models and evaluate them with accuracy, F1, and a confusion matrix • Train two deep-learning models to classify tomato ripeness |
| Graduation Ceremony |
• Share outcomes and reflect on learning across all modules • Celebrate student work and discuss next steps for continued learning |
- Your handouts
- Yield Prediction
- Tomato Classification
- Simple Tomato Classifier
- Advanced Tomato Classifier
The July 24th video is from Dr. Kubota on Grafting and Advanced Technologies in Smart Agriculture!
Ready to take your quiz? Good luck!