flyrank

AI-Powered Content Opportunity Scoring using Machine Learning | FlyRank ML Internship Capstone | Random Forest Regression | Search Intelligence

A Machine Learning repository developed during my FlyRank AI Internship, focused on data engineering and model analytics.

Persistent Task Management REST API built with Node.js, Express.js, SQLite, and Swagger UI. Developed during the FlyRank Backend AI Engineering Internship using real-world educational workflows from Navigant Education Consultants.

FlyRank ML Engineering Internship — Machine Learning Content Opportunity Scoring (Precision@50: 0.740 vs 0.340 Baseline)

My work and assignments for the FlyRank Machine Learning Internship, documenting weekly notebooks, experiments, and the capstone project.

A CRUD REST API built with Python and FastAPI, backed by SQLite for persistent storage. Same endpoints as the in-memory version — now tasks survive a server restart.

Lightweight, persistent RESTful CRUD To-Do List API built with Python, FastAPI, SQLModel, and SQLite. Features automatic database schema creation, pre-seeding, Pydantic input validation, and Swagger UI docs. FlyRank Backend Track (BE-01 & BE-02).

This repository contains a minimal backend server built during my Backend AI Engineering internship training at FlyRank AI. The goal of this task is to practically experience the core Request-Response loop by setting up a lightweight server from scratch.

Implementation of PostgreSQL integration, switching from in-memory storage to a persistent DB repository, and containerizing the stack with Docker Compose as part of the FlyRank training project.

CRUD Task API — evolved from in-memory storage to SQLite to a containerized PostgreSQL stack with Docker Compose, Swagger docs, and staged commits.

A secure REST API built with Express.js and Supabase Auth featuring user signup, login, JWT authentication, protected routes, logout, and Swagger documentation. [ WEEK - 04 ]

Code, tasks, and deliverables for the FlyRank Backend AI Engineering internship

Capstone repo for the FlyRank Frontend AI Engineering internship — weekly deliverables from Frontend AI Engineering + AI Fluency tracks, evolving into a full capstone project.

A CRUD REST API built with Python and FastAPI, backed by PostgreSQL running in Docker. Swaps in a Postgres repository behind the same service/route layer used in the in-memory and SQLite versions — full stack starts with one command: docker compose up.

Official portfolio, applied machine learning research paper, and autonomous decision-support agent for Sohila Khaled Abbas (Applied ML Intern & Search Intelligence Engineer at FlyRank AI | BI Developer).

Machine Learning research project predicting declining web content using the FlyRank ML Internship dataset.

Repository for collected work at FlyRank Internship

My work for the FlyRank AI Machine Learning Internship — running the starter ML pipeline, notebooks and assignments week by week.

Secure REST API built with FastAPI and Supabase Authentication featuring JWT authentication, protected routes, reusable authorization dependencies, and Swagger documentation.

Production-grade usage metering, quota enforcement, and billing engine built with FastAPI, PostgreSQL, and Stripe. Features exactly-once idempotency, micro-cent integer money math, and signature-verified webhook synchronization. FlyRank AI Engineering Capstone.