Case studies and success stories
Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
This Technology Insight will demonstrate how to optimize data analytics and machine learning workloads for Intel® Architecture based data center platforms. Speaker: Pradeep Dubey Intel Fellow, Intel Labs Director, Parallel Computing Lab, Intel Corporation
Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
Apache Spark* (http://spark.apache.org/) is a fast and general engine for large-scale data processing.
How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL) in Linux*The Intel® Data Analytics Acceleration Library (Intel® DAAL) 1, 2 is a software solution for data analytics. It provides building blocks for data preprocessing, transformation, modeling, predicting, and so on.
Using Intel® Data Analytics Acceleration Library to Improve the Performance of Naïve Bayes Algorithm in Python*This article discusses machine learning and describes a machine learning method/algorithm called Naïve Bayes (NB) . It also describes how to use Intel® Data Analytics Acceleration Library (Intel® DAAL)  to improve the performance of an NB algorithm.
How to optimize Caffe* for Intel® Architecture, train deep network models, and deploy networks.
Intel® Data Analytics Acceleration Library (Intel® DAAL) is a software solution that offers building blocks covering all the stages of data analytics, from preprocessing to decision making. The beta version of Intel DAAL 2017 provides support for the Python* language.
In this article, we provide the steps to set up the AWS CloudFormation* environment to train deep networks using the Caffe network.