Rev up AI Pipelines with Intel®-Optimized Python* Libraries
Subscribe Now
Stay in the know on all things CODE. Updates are delivered to your inbox.
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
Get the Software
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
Intel® Distribution for Python*
Develop fast, performant Python* code with this set of essential computational packages including NumPy, SciPy, scikit-learn*, and more.
Get It Now
Build a Deep Learning Environment in Python* with Intel and Anaconda*
Deliver Fast Python Data Science and AI Analytics on CPUs
Parallelism in Python: Dispelling Myths with Tools for Parallelism
Create Your First Neural Network with Python and TensorFlow*
Parallelism in Python Using Numba*: The Fundamentals