XGBoost
MLOps & Infrastructure
Overview
XGBoost is an open-source gradient boosting library that provides an optimized distributed implementation of gradient boosting for structured data. It supports classification, regression, and ranking tasks, and is widely used in data science competitions and production ML. XGBoost offers high performance, parallel tree construction, and handles missing values, making it a standard tool for tabular data ML.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises, API / SDK
- Regions served
- Global
- Categories
- Free, MLOps & Infrastructure, Software & technology, Workflow orchestration, API / SDK, Self-hosted / on-premises, Predictive / classical ML, Functional application
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Deployment options
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- xgboost.ai
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
Spotted something out of date?
Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.