For as long as I’ve started with machine learning, Jupyter Notebooks have been my most loyal sidekick. From data preprocessing to model training, fine-tuning, and testing, Jupyter Notebooks have been there at every step to support me. However, I always knew that there is an entire world beyond these digital pages — a world of deployment and application.
Taking the leap from training a model to actually deploying it might seem intimidating. However, it’s a critical step that transforms a data science project from a theoretical experiment into a practical, real-world application. And I knew I had to take that extra step!