Turning ML Notebooks Into Products from Building VisPilot
Introduction Most machine learning work dies inside a notebook. Brilliant experiments. Impressive metrics. Clever feature engineering. None of it matters if no one outside the data team can actually use the results. This is the core problem VisPilot was designed to...
Building Real-Time Computer Vision Systems a reference from FaceVision
Introduction Most people think computer vision is simple. Upload an image. Run a pre-trained model. Get a bounding box. Done. But real-world computer vision is not a static image problem. It’s a systems engineering challenge — one that requires: real-time inference...
The Future Belongs to Full-Stack Data Scientists — Here’s Why
Introduction Five years ago, the world of data was divided neatly: Data Scientists built models Data Engineers built pipelines Software Developers built applications Analysts built dashboards ML Engineers stitched everything together Those days are gone. Today,...