Problem?

Crypto traders lacked reliable price predictions, relying on outdated models that underperformed in volatile markets, missing profitable opportunities.


Solution!

I developed a deep learning model using RNN architectures and TensorFlow, incorporating attention mechanisms to forecast prices with greater precision.


Result:

Outperformed baseline models by 17% in predictive accuracy, earned 100+ citations in research, and reduced forecasting errors by 15%.