Distributed Machine Learning Techniques for Geospatial Data

Abstract

I was invited to teach a course on distributed machine learning to the Geo-Informatics and Space Technology Development Agency (GISTDA). The curriculum covered fundamental concepts of PySpark, basic deep learning techniques, and practical applications of distributed training using TensorFlow. I also emphasized methods for leveraging Multi-GPU setups and implementing distributed training strategies, particularly in the context of geospatial data analytics, equipping participants with the skills needed to handle large-scale machine learning tasks efficiently.