Machine Learning

Banking as we know it is a chore—a relic of a pre-AI era. We've moved from reactive dashboards to the promise of empathetic AI coaches, but the final evolution is far more radical: a completely invisible financial world.

We're all amazed by what AI can do, but behind the scenes lies a massive, hidden cost. From the energy it takes to train a single model to the shocking amount of water data centers consume, the environmental impact is real and severe.

During my career as a developer, I often wished for a better way to grow. I wanted a coach that could offer constant, personalized feedback on my code, and a way to measure whether I was truly improving or just spinning my wheels.

This technical blog post goes into methodology, showcasing how I leverage Random Forest, LSTM, and Transformer networks to contribute to more robust predictions.