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🧠 LLM pipelines, model training notebooks, and real-world AI/ML deployments with testing

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🤖 AI Engineer Portfolio

This portfolio features advanced AI/ML projects with production-ready pipelines. It covers everything from LLM integration and model fine-tuning to deploying ML services and validating notebooks with CI workflows.

🧠 Highlights

  • LLMs with Hugging Face Transformers
  • Model training and evaluation notebooks
  • MLOps-style workflow testing (nbmake, CI)
  • Checkpointing and model lifecycle
  • AI deployments with FastAPI & Docker

Project List

1. Multilingual Voice Agent for Public Services

Problem

Citizens struggle to access government info in native languages via digital channels.

Solution

Build a voice assistant that:

  • Converts speech to text using Whisper
  • Translates using NLLB (No Language Left Behind)
  • Queries a knowledge base using RAG with LlamaIndex
  • Speaks answers via TTS (Bark or Coqui)
  • Deployable via Twilio Voice or WhatsApp

Goals

  • Serve local languages like Swahili, Luo, Kikuyu, Somali
  • Provide answers about IDs, licenses, schools, etc.
  • Log anonymized usage metrics

2. African News Summarizer and Bias Detector

Problem

News often contains bias and lacks multilingual accessibility.

Solution

Train a summarizer + bias detector:

  • Fine-tune T5 or Falcon on local news corpora
  • Build React frontend to enter URLs and summarize
  • Use Hugging Face Transformers + Langchain

Goals

  • Summarize articles in 3 languages
  • Classify for bias type: political, regional, tone
  • Suggest counterpoints and sources

3. Medical Imaging Assistant for Understaffed Clinics

Problem

Clinics lack radiologists to interpret X-rays and CT scans.

Solution

Build a diagnostic model using:

  • YOLOv8 + fastai for object detection
  • Train on open datasets (NIH ChestX-ray14, VinDr)
  • Deploy via Streamlit or Gradio interface

Goals

  • Identify common findings (TB, pneumonia, fractures)
  • Allow image uploads from mobile
  • Generate PDF reports

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