Machine Learning Engineer

Hi, I'm AIRaML

I build end-to-end ML pipelines — from raw data to deployed prediction APIs with interactive frontends. Every project below is live and testable.

4
Live Projects
3
Datasets
96.7%
Best Accuracy
Auto-ML
Pipeline
View ProjectsGitHub

Projects

Live ML Apps — click to predict

Platform

ML Unified Platform

4
Models

One app, four models. Select Iris classifier, Titanic survival predictor, Diabetes risk model, or Insurance premium estimator from a sidebar — all served from a single schema-driven FastAPI backend with dynamic forms.

ModelMulti-Model
Features26
4 Datasets · 26 Features
PlatformFastAPISchema-DrivenClassificationRegression
Launch App

All projects are hosted on Render free tier — first load may take ~15s to spin up.

About

Building ML from scratch
to production

I'm a machine learning engineer focused on building complete, deployable ML systems — not just notebooks. Each project here runs a full pipeline: data preprocessing, feature engineering, model selection, training, and a REST API served with FastAPI.

The frontends are live, interactive, and dark/light themed. The Auto-ML pipeline bootstrapper generates new project templates from any CSV dataset in seconds.

Languages

PythonTypeScriptSQL

ML / Data

Scikit-learnPandasNumPyXGBoostLightGBM

Backend

FastAPIUvicornREST APIs

Frontend

Next.jsReactTailwind CSSVanilla JS

DevOps

DockerRenderVercelGitHub Actions