Intel® AI Analytics Toolkit and XGBoost for Predictive Modeling
Subscribe Now
Stay in the know on all things CODE. Updates are delivered to your inbox.
Explore predictive modeling techniques based on decision trees using the Intel® AI Analytics Toolkit (AI Kit). Popular decision-tree algorithms are used to examine training challenges when data sizes increase. The AI Kit can help circumvent the challenges.
Starting with a basic decision tree and advancing to techniques that balance the tradeoffs of speed and accuracy, this workshop—hosted on Intel® Developer Cloud—shows how the AI Kit can improve predictive modeling implementations.
Workshop topics include:
- Capabilities of the AI Kit and how to install it
- Decision trees and how to use the AI Kit to create them
- Performance features of XGBoost and how to use them
Intel® AI Analytics Toolkit
Accelerate end-to-end machine learning and data science pipelines with optimized deep learning frameworks and high-performing Python* libraries.
Get It Now
New AI Reference Kits Enable Scaling of Machine Learning and Deep Learning Models
Accelerate Linear Regression Models for Machine Learning
Hunt Dinosaurs with Intel® AI Tools for Computer Vision
Machine Learning Tricks to Optimize CatBoost* Performance Up to 4x
Optimize End-to-End AI Pipelines