Week 4

Machine Learning & Artificial Intelligence

Introduction

This week we move from managing agricultural data to using it for prediction and learning. We introduce the foundations of machine learning and AI and begin exploring how these approaches can support agricultural applications.

Learning goals

  1. Understand the basic concepts of machine learning and artificial intelligence

  2. Distinguish between supervised and unsupervised learning

  3. Set up a mini individual project

  4. Explore packages, Hugging Face models, and model serving

Lecture - ML and AI Basics

Introduction to machine learning and artificial intelligence, with examples from agriculture.

Topics include supervised and unsupervised learning and their applications to agricultural data.

Lab - Project Mini: Packages, Hugging Face & Model Serving

Set up the mini individual project and explore Python packages, Hugging Face models, and basic model serving.

Discussion - Ethical and Efficient Use of AI

How can we use AI effectively, responsibly, and efficiently in agricultural data science?

Assignment

Organize your data, set up your GitHub repository, and submit a one-page concept note outlining your mini individual project.

Looking ahead

Next week we will begin working on the mini individual projects, applying the tools and concepts introduced so far.

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