# Pushing the Technical Frontier: From Overwhelmingly Large Data Sets to Machine Learning

## TL;DR

This paper discusses how machine learning techniques can address the big data challenges posed by large galaxy surveys, aiding in panchromatic galaxy modeling with next-generation facilities.

## Contribution

It provides a conceptual overview of applying machine learning to large-scale galaxy data analysis, highlighting potential solutions for upcoming astronomical surveys.

## Key findings

- Machine learning can improve data processing efficiency.
- ML methods enable better galaxy property estimation.
- Potential to handle data volume from next-generation surveys.

## Abstract

This paper summarizes my thoughts, given in an invited review at the IAU symposium 341 "Challenges in Panchromatic Galaxy Modelling with Next Generation Facilities", about how machine learning methods can help us solve some of the big data problems associated with current and upcoming large galaxy surveys.