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.
- 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
Citizens struggle to access government info in native languages via digital channels.
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
- Serve local languages like Swahili, Luo, Kikuyu, Somali
- Provide answers about IDs, licenses, schools, etc.
- Log anonymized usage metrics
News often contains bias and lacks multilingual accessibility.
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
- Summarize articles in 3 languages
- Classify for bias type: political, regional, tone
- Suggest counterpoints and sources
Clinics lack radiologists to interpret X-rays and CT scans.
Build a diagnostic model using:
- YOLOv8 + fastai for object detection
- Train on open datasets (NIH ChestX-ray14, VinDr)
- Deploy via Streamlit or Gradio interface
- Identify common findings (TB, pneumonia, fractures)
- Allow image uploads from mobile
- Generate PDF reports