Intel® and Anaconda®: Python Data Science at Scale | Intel® On | Intel Software

Опубликовано 8 июня 2022, 3:26

Intel® and Anaconda® have partnered to bring high-performance Python optimizations with simple installations. Rachel Oberman and Todd Tomashek of Intel, and Albert DeFusco of Anaconda, show how with minimal code changes you can accelerate pre-processing, model training, and model inference. See the power of this end-to-end solution in action using the New York City Taxi dataset.

By simply using Intel packages available in the Anaconda defaults channel, you can speed model development using large datasets from hours to minutes.
Learn from Rachel Oberman, Intel AI Technical Consulting Engineer, Todd Tomashek, Intel Machine Learning Engineer, and Albert DeFusco of Anaconda, as they explain:
• What this collaboration has produced
• What kinds of performance improvements have been achieved from pre-processing with Modin to training and inference with scikit-learn and PyTorch
• How to predict how much New York City taxi rides will cost using a 58GB dataset of 380 million rides – in a matter of minutes
• How to find and install these tools in Anaconda

Install Intel oneAPI AI Analytics Toolkit with Anaconda: intel.ly/3O2xcU8

Intel oneAPI AI Analytics Toolkit Code Samples: bit.ly/3GZ555M

Intel Optimized Packages Information on the Anaconda Defaults Channel: bit.ly/3msfI7S

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Intel® and Anaconda®: Python Data Science at Scale | Intel® On | Intel Software