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chonzadaniel/README.md

πŸ‘‹ Hi, I'm Emmanuel Daniel Chonza

I'm a Data Scientist and Generative AI Practitioner passionate about building impactful solutions using NLP, Deep Learning, and Machine Learning. My work explores how AI can solve real-world problemsβ€”from sentiment analysis to Retrieval-Augmented Generation (RAG) systems.

πŸ”­ Current work and Accomplishment:

  • Fine-tuning and evaluating LLMs for custom NLP tasks
  • Scaling RAG pipelines with LlamaIndex and semantic search
  • Improving ML model fairness in imbalanced text classification
  • Deploying real-time AI applications with Streamlit and Slack.
  • Machine learning training using MLflow

🌱 In the pipeline:

  • Parameter-Efficient Fine-Tuning (PEFT): QLoRA, LoRA, IA3
  • Vector databases for context-aware search (e.g., FAISS, ChromaDB)
  • Building production-ready GenAI apps and dashboards

πŸ‘― I’m looking to collaborate on:

  • Applied NLP (especially underrepresented text domains), CV, ML, projects
  • End-to-end MLOps/LLMOps pipelines
  • AI/ML research with community impact

πŸ’‘ Featured Projects:

  • Credit Card Fraud Detection Classifier - This project develops a robust machine learning pipeline for credit card fraud detection, leveraging a highly imbalanced dataset. Detecting fraudulent transactions is crucial for financial institutions to minimize monetary losses and protect customer assets.
  • Resume & Job Application Advisor - An agentic system powered by CrewAI and open-source LLMs that helps job seekers improve their resumes, discover current job openings, generate tailored cover letters, and prepare for interviews β€” all in a single interactive Streamlit app.
  • Racist Tweet Classifier β€” NLP pipeline with SymSpell correction, oversampling, stratified cross-validation & Streamlit UI
  • Car Price Prediction β€” Regression modeling using XGBoost and feature engineering on real marketplace data
  • RAG Toolkit β€” Experimenting with OpenAI, BGE, and LlamaIndex to build smarter retrieval pipelines
  • Image Classifier - An End-to-End Image Classifier for 101 foodvision images capable of predicting the image label among the 101 foodvison image labels, e.g. sushi, pizza, etc. and a dog vision project in similar fashion using the 120 Stanford Dog breeds Image dataset

πŸ“« How to reach me:

πŸ“© LinkedIn β€’ βœ‰οΈ chonzadaniel@yahoo.com β€’ 🌐 GitHub Projects


πŸ’¬ Ask me about NLP, Computer Vision, Machine Learning, Transformers, GenAI, fine-tuning LLMs, and practical AI deployment!

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