Data enrichment Tutorials and Publications

Learn how to use Upgini to enrich your dataset with powerful, informative features using Large Language Models (LLMs). This guide demonstrates a significant boost in predictive performance—an uplift of 0.1—all achieved with automated feature engineering.

This tutorial walks you through a sales forecasting project using 5 years of product sales data. Learn to forecast future sales for the next 3 months with a gradient boosting algorithm and Upgini’s data enrichment features.

Discover five popular libraries for enriching ML models with open data, including holidays, stock data, and weather information. This in-depth review features libraries like holidays, yfinance, meteostat, pandas-datareader, and upgini.

Using the Intuit dataset from OpenML, this tutorial shows how to predict email responses. Enrich your model with Upgini to improve prediction accuracy with a binary target variable for response.