WinML evaluates models in the ONNX* format—an open format for machine learning models. It allows you to interchange models between various machine learning frameworks and tools.
WinMLTools (an extension of ONNXMLTools and TF2ONNX) enables you to convert machine learning models created with different training frameworks into the ONNX format.
Learn to build a simple Universal Windows Platform application that uses a trained machine learning model to recognize a numeric digit drawn by the user.
Create a simplified version of the SqueezeNet object detection sample.
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.
Notice revision #20110804