Deep Learning in Deep Space

This document discusses the use of machine learning techniques for analyzing astronomical and earth observation data. It notes that large sky survey projects generate huge amounts of data that exceeds our ability to analyze using traditional methods. Machine learning can help process and extract insights from this big data. Specifically, the document discusses how convolutional neural networks have achieved 98% accuracy in classifying galaxy images from sky surveys. It also provides examples of applying machine learning to tasks like terrain classification from earth observation satellite imagery.