XGBoost

XGBoost 3.1.3 on Ubuntu 24.04 with Free Maintenance Support by bCloud is a powerful, high performance machine learning solution available through the AWS Marketplace. It is designed for building accurate and scalable models for real world data problems. Offered as a ready to run environment with optional maintenance support by bCloud, this solution helps users get started quickly without the overhead of manual setup or configuration.

XGBoost is an open source gradient boosting library known for its speed, efficiency, and ability to handle large datasets. It builds decision trees sequentially, where each new tree improves on the errors of the previous ones, resulting in strong and reliable predictive models. With a C++ core and support for parallel processing on both CPU and GPU, XGBoost consistently delivers excellent performance for classification, regression, and ranking tasks.

This Ubuntu 24.04 based AMI is optimized for the AWS Cloud Marketplace, making it easy to deploy on EC2 instances and integrate with other AWS services. It is well suited for data scientists, machine learning engineers, and enterprises that want a stable, cloud ready environment for gradient boosting workloads.

Available AWS Marketplace Options for XGBoost

XGBoost on Ubuntu 24.04 with Maintenance Support by bCloud
This is a lightweight, single purpose AMI focused on XGBoost workloads. It is ideal if you want minimal overhead, fast startup, and optional professional support from bCloud. It works well on both CPU and GPU based EC2 instances.

Anaconda Platform Business Cloud SaaS
Anaconda provides a managed SaaS platform that includes XGBoost as part of the Anaconda distribution. This option is best for organizations that need enterprise level governance, package lifecycle management, security scanning, and role based access control across multiple users and teams.

Deep Learning Base GPU AMI on Ubuntu 24.04
This GPU optimized AMI is designed for high throughput training and experimentation. It comes preinstalled with XGBoost along with popular frameworks like PyTorch and TensorFlow, making it a great choice if you want XGBoost as part of a broader deep learning and AI environment.

Key Differences and When to Choose Each
Choose the XGBoost AMI by bCloud if you want a simple, efficient, and production ready setup focused specifically on gradient boosting, with the option of professional maintenance support.

Select the Deep Learning Base GPU AMI if you need GPU accelerated training and want XGBoost alongside a full stack of deep learning libraries for experimentation and research.

Why XGBoost on Ubuntu 24.04
XGBoost runs smoothly on Ubuntu 24.04 and integrates well with AWS infrastructure. It supports NVIDIA GPU acceleration using CUDA, enabling significant performance gains for large and complex datasets. Installation is flexible through pip, conda, or pre configured Marketplace AMIs, allowing users to choose the setup that best fits their workflow.

Key advantages include high accuracy on structured data, excellent scalability, built in regularization to reduce overfitting, and strong portability across cloud and on premise environments.

Highlights

• XGBoost delivers fast and scalable performance with support for both CPU and GPU processing.
• Built in regularization helps improve model generalization and accuracy.
• Supports classification, regression, and ranking use cases across many industries.
• Optimized for deployment on the AWS Cloud Marketplace for fast and reliable scaling.