Artificial Intelligence has been at the centre of my career for the better part of a decade. I’ve built NLP models for financial news, deployed deep learning pipelines to production, and more recently led Generative AI prototype developments. It’s a field that moves fast — and that’s exactly what makes it exciting.

What This Series Is About

This series covers AI and Machine Learning from both a practical and conceptual angle. Expect posts on:

  • Machine Learning fundamentals — from linear regression to gradient boosting
  • Deep Learning & NLP — LSTMs, transformers, and language models
  • MLOps — how to take models from notebook to production reliably
  • Generative AI — LLMs, prompt engineering, and real-world applications
  • Lessons from the field — what actually works when you’re shipping models at scale

My Take on AI

AI is not magic, and it’s not going to replace good engineering judgment. The most impactful work I’ve done has always come from combining solid ML knowledge with strong software engineering practices — understanding the data, designing reliable pipelines, and knowing when not to use a complex model.

I’ll be writing from that perspective: practical, grounded, and honest about the trade-offs.

Articles in This Series

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