Vancouver, BC–May 18, 2017 — ActiveState, the open source languages company, announced today the inclusion of Intel®’s Machine Kernel Library (MKL) Performance-Optimizations for data science and machine learning Python packages in ActivePython 2.7.13 and ActivePython 3.5.3. In the latest release, NumPy, SciPy, matplotlib, and theano packages now run faster by internally leveraging the multi-threading and vectorization features of Intel’s MKL in ActivePython.
“Intel MKL allows Python users to take advantage of the Intel® Advanced Vector Extension 2 (Intel® AVX2) instructions in our multicore and many-core processors for machine learning and other numerical computing, with no changes to their existing code,” said Robert Cohn, Senior Principal Engineer, Intel Corporation. “Data scientists and technical compute users are enabled to tackle the most demanding computational tasks while using Python.”
With the proliferation of smart devices and the large volume of data generated by them, companies are leveraging data and using machine learning to provide their customers with a better experience when using their applications. In addition, computation speed has increased so now organizations are able to do a lot more with neural networks than they could in the past.
According to Gartner, “the volume of inquiry calls from Gartner clients about AI, advanced machine learning and related topics increased by 200% between 2015 and 2016…By 2020, 20% of enterprises will employ dedicated people to monitor and guide machine learning (such as neural networks). The notion of training rather than programming systems will become increasingly important.”*
“To ensure that our customers are able to leverage the advancements of deep learning, the latest release of ActivePython now includes TensorFlow and theano, some of the most popular Python packages in the area of machine learning. We have also added Jupyter notebook support that enables data scientists to share their code and collaborate with colleagues,” said Tom Radcliffe, Vice-President of Engineering at ActiveState. “This year, we’ve brought continual refinements to ActivePython, with each release bringing greater power to data science teams.”
In addition, ActiveState has added more security and data engineering Python packages in the ActivePython 2.7.13 and 3.5.3 distributions. The service-identity package, that works with OpenSSL in Python, prevents a known man-in-the-middle attack problem. ActivePython now also includes Luigi, Dask, and Apache Airflow, Python packages that make it easier for Data Engineers to schedule jobs, author pipelines, and monitor these tasks.
Commercially supported and quality-assured, ActiveState performs license reviews and vulnerability scans to ensure they are providing their customers with the most secure Python packages.
Learn more and download ActivePython Community Edition for free here.
*Gartner, Top 10 Strategic Technology Trends for 2017: Artificial Intelligence and Advanced Machine Learning, 15 March 2017.
ActiveState, the open source languages company, believes that enterprises gain a competitive advantage when they are able to quickly create, deploy and efficiently manage software solutions that immediately create business value, but they face many challenges that prevent them from doing so. The company is uniquely positioned to help address these challenges through our experience with enterprises, developers and open source technology. ActiveState is proven for the enterprise: more than 2 million developers and 97 percent of Fortune 1000 companies use ActiveState’s end-to-end solutions to develop, distribute, and manage their software applications written in Perl, Python, Ruby, Go, Node.js, Lua, Tcl and other dynamic languages. Global customers like Cisco, CA, HP, Bank of America, Siemens and Lockheed Martin trust ActiveState to save time, save money, minimize risk, ensure compliance, and reduce time to market. To learn more visit, ActiveState.com.
Jesse Casman for ActiveState