Isaiah Ogooluwa Bakare

AI Engineer  ·  Full-Stack Developer  ·  Data Scientist

   

     

profile = {
    "name":     "Isaiah Ogooluwa Bakare",
    "alias":    "Praise Ogooluwa",
    "role":     "AI Engineer · Full-Stack Developer · Data Scientist",
    "school":   "Lagos State University — BSc Mathematics",
    "website":  "https://praiseogooluwa.com",
    "building": ["Assignify (assignify.com.ng)", "AI Resume Matcher", "GMC Intelligent Chatbot"],
    "stack":    ["Python", "FastAPI", "React", "LLMs", "RAG Pipelines"],
    "focus":    "Production-grade AI applications & LLM integrations",
    "goal":     "International career in Data Science & Machine Learning",
}

Languages

AI / ML

Backend & Infrastructure

Frontend

Founder · Full-Stack · Live in Production

Founded and built a production full-stack academic management platform for Nigerian university lecturers — covering assignment creation, student submissions, grading, multi-file uploads, and reporting. Engineered end-to-end with security-hardened production features: rate limiting, CORS lockdown, Cloudflare Turnstile CAPTCHA, and branded transactional email via Resend.

React TypeScript FastAPI Supabase Vercel Render Tailwind

LLM · RAG · Full-Stack

Full-stack LLM-powered application that scores and ranks resumes against job descriptions using a RAG pipeline, vector similarity search, and NLP-based skill extraction. Delivers ranked candidate recommendations with structured actionable feedback — end-to-end production AI system design.

Python Anthropic SDK ChromaDB RAG FastAPI React

NLP · TensorFlow · Streamlit · GOMYCODE Final Project

Designed and trained an NLP-powered chatbot on an educational consultation dataset using TensorFlow/Keras with intent classification, sentiment analysis, and NER. Full pipeline from data collection and preprocessing (tokenization, stemming, lemmatization) through model training to live Streamlit deployment.

Python TensorFlow Keras NLP Streamlit

Machine Learning · Classification · Streamlit

Built a Financial Inclusion Prediction app using a trained classification model to predict bank account ownership across East African countries from demographic data. Also developed a Telecom Churn Prediction system using Random Forest with label-encoded categorical features and real-time prediction via Streamlit.

Python scikit-learn Random Forest Streamlit Pandas

Machine Learning · Healthcare · Classification

Built a classification model to predict patient no-shows for medical appointments using real-world booking and demographic data, applying feature engineering and EDA to optimize predictive accuracy.

Python scikit-learn Pandas EDA Feature Engineering

 

Building the future, one commit at a time — Lagos → World