14:00-16:00 pm September 7th, 2023
overview:
In this tutorial we introduce the field of geospatial machine learning by first going over the geospatial data primitives then solving a machine learning problem in an "end-to-end" fashion.
We aim to cover the following:
Introduction to geospatial data: vector and raster data primitives.
Problem framing: introducing the problem that we are going to solve.
Approach 1: Tabular Learning with LightGBM.
Data acquisition and preprocessing: we will get the data and preprocess it for machine learning.
Model fitting: we will fit a model to the data and conduct hyperparameter search.
Model evaluation: we will evaluate the model on the test data.
Inference: we will predict the output for the test data.
Approach 2: Deep Learning with a Sequence-to-One model.
Topics:
Content: Geospatial Data Analysis, Computer Vision, Tabular Data.
Level: Beginner, Intermediate