About AstroLatent

AstroLatent — Learning astrophysics through data, code, and curiosity.

Astrophysics meets ML — one dataset at a time. Each post documents what I figured out, how I did it, and what surprised me.

Topics I explore

• Astronomical surveys & datasets — Digging into Gaia, SDSS, DESI, JWST and learning to query real sky data
• Spectral classification, SED fitting, photometry, time-series — Trying the methods, understanding the maths, documenting the pitfalls
• AI & Machine Learning — Applying modern ML techniques to real astrophysical datasets
• Python for astrophysics — Astropy, Astroquery, Specutils, and the scientific Python ecosystem

What this is

A learning journal — a lab notebook from someone exploring computational astrophysics in the open. Notes can be partial, exploratory, or in-progress. Not everything is a polished article.

If you find something useful here, that is a bonus.