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appliedalgorithmslab/README.md

Applied Algorithms Lab

Python backend engineering and data systems projects focused on:

  • REST APIs over structured data
  • database-driven applications
  • scalable Python services
  • full-stack web platforms (React + backend APIs)
  • distributed data processing

Technical stack

Python, SQL, Django, FastAPI, SQLAlchemy, PostgreSQL, Dask, AWS, React, JavaScript, HTML/CSS

Focus

The repositories here emphasize clean backend architecture, structured data access, scalable processing workflows, and full-stack application development.

Notes

These repositories contain demonstration implementations and non-proprietary examples. Proprietary production systems and client-specific algorithms are not included.

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  1. mini-slashdb mini-slashdb Public

    Lightweight FastAPI + SQLAlchemy backend exposing relational data through REST-style endpoints for full-stack web applications

    Python

  2. distributed-ml-dask distributed-ml-dask Public

    Python

  3. ml-model-benchmarking ml-model-benchmarking Public

    Reproducible machine learning benchmarking framework for comparing models across datasets and evaluation metrics.

    Python

  4. ml-debugging-exercises ml-debugging-exercises Public

    Examples of common machine learning failure modes, debugging strategies, and corrected implementations.

    Python