Skip to content

Bi-weekly decoded AI papers and implementation notes for AI engineering.

Working code, honest tradeoffs, and real datasets — from a practitioner applying recent AI/ML research under the same constraints you face.

What you'll get

Who this is for

Practitioners applying AI in public health, data science, and adjacent fields — building real systems with standard tools and modest compute, under the same constraints most teams actually face.

The Decoded Dispatch

Bi-weekly implementation notes for practitioners applying AI in public health and data science.

    No spam. Unsubscribe at any time.

    About the author

    I'm Mayer Antoine. DecodedPapers documents how I take architectures and techniques from recent AI/ML papers, implement them on real datasets, and adapt them to solve practical problems. Every post is a working implementation with documented decisions, adaptations, and tradeoffs — something you can run, customize, and carry into your own work.

    Recent issues

    The Decoded Dispatch

    Bi-weekly implementation notes for practitioners applying AI in public health and data science.

      No spam. Unsubscribe at any time.