✨ Read this must-read post from Hacker News 📖 📂 **Category**: ✅ **What You’ll Learn**: Tabular data constitutes the backbone of enterprise data infrastructure and powers a significant fraction of critical predictive machine learning applications. From predicting customer churn to identifying financial fraud, tabular regression and classification tasks are ubiquitous. For years, supervised tree-based algorithms like AdaBoost, XGBoost and random forests, to name a few, have historically dominated this space, offering robust performance on structured data.However, the lifecycle of deploying these traditional models presents a significant bottleneck. Fitting an XGBoost model to a new dataset is not merely a matter…
