  The ages of star clusters and co-moving stellar groups contain essential
information about the Milky Way. Their special properties make them excellent
tracers of galactic structure and key components to unlocking its star
formation history. Yet, even though the importance of stellar population ages
has been widely recognized, their determination remains a challenging task
often associated with highly model-dependent and uncertain results. We propose
a new approach to this problem, which relies on empirical isochrones of known
clusters extracted from high-quality observational data. These purely
observation-based data products open up the possibility of relative age
determination, free of stellar evolution model assumptions. For the derivation
of the empirical isochrones, we used a combination of the statistical analysis
tool principal component analysis for preprocessing and the supervised machine
learning method support vector regression for curve extraction. To improve the
statistical reliability of our result, we defined the empirical isochrone of a
color-magnitude diagram (CMD) of a cluster as the median calculated from a set
of bootstrapped curves. We provide empirical isochrones in all Gaia DR2 and DR3
color combinations for 83 nearby clusters, paving the way for a relative
comparison between individual stellar populations based on an age-scaling
ladder of empirical isochrones of known clusters. Due to the precision of the
available observational data, we report accurate lower main sequence empirical
isochrones for many clusters in our sample, which are of special interest as
this region is known to be especially complex to model. We validate our results
by comparing the extracted empirical isochrones to cluster ages in the
literature. We also investigate the added information that empirical isochrones
covering the lower main sequence can provide on two case studies.
