This lesson is a template for creating geohackweek lessons.
It is based on the lesson template used in Data Carpentry and Software Carpentry workshops,
| 09:00 | Machine Learning with GIS application (a Computer Vision Problem) | What is machine learning? How can it be applied to the GIS landscape? What are some use cases? |
| 09:15 | Supervised Learning: Tree-based methods |
What is the difference between a model and a machine learning algorithm?
Which of the above is associated with learning? What are some characteristics of tree-based learning methods? |
| 09:30 | Supervised Learning: Support vector machines |
What is a tensor?
What might be some characteristics of vector-based learning methods? |
| 09:40 | Land Classification with Supervised Machine Learning | How can I create a simple image pixel classifier using python? |
| 10:05 | Evaluating ML Models | |
| 10:10 | Deep Learning | |
| 10:15 | Machine Learning Resources | What are some basic examples of libraries to explore? |
| 10:20 | Finish |