Machine Learning

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