Rev up AI Pipelines with Intel®-Optimized Python* Libraries

Calling all Python* developers focused on AI and machine learning: Advance your Python coding skills; achieve highly efficient multithreading, vectorization and memory management; and scale scientific computations across a cluster using the optimized packages found in Intel® Distribution for Python*.

In this session, learn how to:

• Achieve drop-in, end-to-end acceleration for your AI and data science pipelines
• Seamlessly scale pandas workflows across multi-node dataframes
• Increase machine learning model accuracy and performance with Intel®-optimized scikit-learn* algorithms and XGBoost

Skill level: intermediate to advanced

This webinar uses familiar Python tools and frameworks available as part of the Intel® AI Analytics Toolkit. Alternatively, you can download stand-alone versions:

• Intel Distribution for Python
• Intel® Distribution of Modin* (available through a repository, PIP*, or Anaconda*)
• Intel® Extension for Scikit-learn*
• XGBoost Optimized for Intel Architecture