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clappy203/README.md

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About Me

AI / ML / NLP engineer with an M.Sc. in Applied Artificial Intelligence (University of San Diego) and 6+ years delivering data-driven solutions in financial services. I build across the full stack of modern AI - from classical machine learning and NLP to Retrieval-Augmented Generation (RAG) and multi-agent LLM systems.

  • Currently an AI Backend Engineer building a context-aware RAG curriculum-generation system (OpenAI + LangChain + ChromaDB) in a Carnegie Mellon University research collaboration.
  • Interests: RAG architecture, agentic AI, applied NLP, model deployment, and Responsible AI.
  • Domain depth in financial services - AML/ODD compliance, credit risk, and fraud analytics.
  • Conference speaker at Build Stuff (2024) on process automation with Power Platform Tools and it's adoption in compliance workflows.

Tech Stack

Generative AI & Agents

LangChain LangGraph OpenAI RAG ChromaDB

Machine Learning & NLP

PyTorch TensorFlow HuggingFace scikit-learn spaCy

Data & MLOps

Python SQL FastAPI MLflow Docker Databricks Snowflake AWS

Visualisation

Streamlit Power BI Tableau


Featured Projects

Project What it does Stack
Multi-Agent Investment Research Assistant M.Sc. capstone - 4-agent LLM system (Planner, Router, Analyst, Evaluator) that turns real-time financial news into investment insights with an evaluator-optimizer loop. LangGraph, OpenAI API, financial APIs
Drug-Effectiveness Sentiment Analysis (NLP) Compared TF-IDF, Word2Vec & LSTM for sentiment classification, reaching 95%+ accuracy on drug-review text. scikit-learn, VADER, spaCy
Diabetes Readmission Prediction + FastAPI XGBoost/MLP models tracked with MLflow and served as a production REST API. XGBoost, MLflow, FastAPI
Fintech Credit Risk Data Pipeline Containerized ETL that ingests credit-risk data into PostgreSQL for reproducible model training. Python, PostgreSQL, Docker
Climate & Weather Data Pipeline Scalable backend pipeline for real-time and historical weather data feeding climate & AI systems. Python, ETL
House Price Prediction API End-to-end ML model deployment with performance tracking. Python, ML

GitHub Stats


Education & Certifications

  • M.Sc. Applied Artificial Intelligence, University of San Diego (2026)
  • M.Sc. Project Management, Ahmadu Bello University, Zaria (2019)
  • AWS Certified AI Practitioner | DASCA Senior Big Data Analyst (SBDA) | Alteryx Core | Data Engineering (Turing College)

Let's build something intelligent together.

Pinned Loading

  1. House-Price-Prediction-API House-Price-Prediction-API Public

    illustrates how to deploy end to end machine learning model and performance tracking

    Python

  2. climate-weather-data-pipeline climate-weather-data-pipeline Public

    A scalable, backend pipeline for ingesting, storing, and analyzing real-time and historical weather data to support climate simulation and AI systems.

    Python

  3. Fintech-credit-data-pipeline Fintech-credit-data-pipeline Public

    A containerized Python ETL pipeline for automated, reproducible ingestion of Kaggle credit risk datasets into PostgreSQL, enabling reliable training and testing data preparation across environments

    Python

  4. Diabetes-Readmission-Prediction-FastAPI-Model-Deployment Diabetes-Readmission-Prediction-FastAPI-Model-Deployment Public

    Jupyter Notebook

  5. Drug-Effectiveness-Sentiment-analysis-Prediction-Using-NLP-Techniques Drug-Effectiveness-Sentiment-analysis-Prediction-Using-NLP-Techniques Public

    Jupyter Notebook 1

  6. Stock-trading-python-app Stock-trading-python-app Public

    This uses the Polygon.io API to extract data about stocks

    Python