Intel® oneAPI Data Analytics Library
Learn from community members on how to build compute-intensive applications that run efficiently on Intel® architecture.

Samples on Github

Ilya_B_Intel
Employee
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Intel® Data Analytics Acceleration Library has a set of samples available, which demonstrate various use cases since the first version:
https://software.intel.com/en-us/product-code-samples

Starting from Intel DAAL 2018 release we made samples available on Github*:
https://github.com/01org/daal/tree/daal_2018/samples

These Intel® DAAL samples are a collection of code samples for various algorithms that you can include in your program and immediately use: 

  • with the Intel® MPI Library in C++ or Python* application
  • on the Hadoop* cluster in a Java* application
  • on the Spark* cluster in Scala, Java* or Python* application
  • with a MySQL* database in a C++ application
  • with a KDB+* database in a C++ application
  • to create the most common neural network topologies, such as LeNet*, GoogleNet*, AlexNet*, ResNet-50* in a C++ or Python* application
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Ilya_B_Intel
Employee
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Scala samples for Spark* were first introduced in this release. They were designed with ease of use and ease of integration for existing MLlib users in mind. You can find more details on that topic in dedicated article here: https://software.intel.com/en-us/articles/intel-data-analytics-acceleration-library-intel-daal-how-to-use-with-apache-spark

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