How to optimize Caffe* for Intel® Architecture, train deep network models, and deploy networks.
Get recipes for installing development tools and libraries on various platforms for the Python library.
Nervana has joined Intel
The promise of artificial intelligence has captured our cultural imagination since at least the 1950s—inspiring computer scientists to create new and increasingly complex technologies, while also building excitement about the future among regular everyday consumers.
From safe roads to enjoyable commutes, automated driving is poised to change lives and society for the better.
As the leading framework for Distributed ML, the addition of deep learning to the super-popular Spark framework is important, because it allows Spark developers to perform a wide range of data analysis tasks—including data wrangling, interactive queries, and stream processing—within a single framework. Three important features offered by BigDL are rich deep learning support, High Single Node Xeon...
This article describes a common type of regression analysis called linear regression and how the Intel® Data Analytics Acceleration Library helps optimize this algorithm on Intel® Xeon® processors.
Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.
Learn how to configure the Eclipse* IDE to build the C++ code sample, along with a code walkthrough based on the AlexNet deep learning topology for AI applications.
Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.