The Intel® Distribution for Python* 2018 has officially been released!

The Intel® Distribution for Python* 2018 has officially been released!

The Intel® Distribution for Python* 2018 has officially been released! 

The new release brings Python 3.6 support, OpenCV and Intel® Performance Primitives (IPP) support, a tech preview of daal4py, and various package version updates.  

Please refer to the release notes for more information on the release.  

In addition, several other new articles have been posted:

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For more complete information about compiler optimizations, see our Optimization Notice.

NOTE on updating:

In order to update from an earlier version of Intel(R) Distribution for Python using conda, you will need to use the "conda install" command to update from python 3.5 to python 3.6. Using "conda update" will NOT work because it does not update python itself.

> conda install python=3.6 -c intel

Hi, I just download and installed IDP 2018. It seems daal functionality are not usable anymore in scikit-learn package. Is it missed or there is something changed? Thank you.

Hi, official developer

it's glad to hear Intel Python 2018 to be released. But I have a problem, according to https://software.intel.com/en-us/articles/intel-optimized-packages-for-the-intel-distribution-for-python , official benchmark nice result(https://software.intel.com/en-us/distribution-for-python/features) have any code to be provided?  

About FFT-benchamrk, can refer to: https://github.com/IntelPython/ , but other test case no found. Thanks !

Quote:

yan c. wrote:

Hi, official developer

it's glad to hear Intel Python 2018 to be released. But I have a problem, according to https://software.intel.com/en-us/articles/intel-optimized-packages-for-the-intel-distribution-for-python , official benchmark nice result(https://software.intel.com/en-us/distribution-for-python/features) have any code to be provided?  

About FFT-benchamrk, can refer to: https://github.com/IntelPython/ , but other test case no found. Thanks !

Hi,

The majority of the benchmarks are under the github link you specified (i.e. Black Scholes, FFT), and the scikit-learn benchmarks can also be found on the official github for scikit-learn (https://github.com/scikit-learn/scikit-learn/tree/master/benchmarks).

Thanks,

-David

Any docs/samples for Intel Python IPP library?

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