Techniques to Accelerate NumPy & SciPy in Intel® Distribution for Python*

Get high-performance Python* at your fingertips with Intel® Distribution for Python*, and experience significant speedups for two of the most popular data science packagesNumPy and SciPy—with Intel® Math Kernel Library (Intel® MKL).

NumPy and SciPy are at the heart of scientific computing with Python. And in less than 4 minutes, software development engineer Oleksandr Pavlyk covers the key functionalities of these Intel-optimized packages for fast Fourier transforms, arithmetic and transcendental UMath functions, and memory optimizations. Plus, he discusses the power of Intel MKL for numerical computing, including how it accelerates NumPy and SciPy, and how to use it directly from the Intel Distribution for Python.

Be sure to download both tools. They’re free.

Performance varies by use, configuration, and other factors. Learn more at www.Intel.com/PerformanceIndex.