Get near-native speed from your AI and data science workloads—even in accelerated computing environments—with minimal code changes.

Calling all Python developers focused on AI/ML. 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.

Attend this session to advance your Python coding skills, including developing for accelerated compute with Data Parallel Python technologies.

You will be able to:

• Achieve drop-in acceleration—end-to-end—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

Sign up today.