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ActiveState
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ActiveGo is here! We are excited to announce the launch of ActiveGo, the only commercially supported Go distribution in the world! Download the free Community Edition here: http://bit.ly/2rJRZ9c
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Heading into PyCon, we wanted to put together something to demonstrate some of the excellent Python packages that are available in the machine learning space as well as showing off some of the newly integrated Intel® Math Kernel Library (MKL) optimizations in the latest ActivePython release. That demo became “NeuroBlast”, a classic arcade space shooter game that features enemies powered by machine learning. It was a fun way to get folks engaged at our booth and to learn about what’s available in the incredible Python ecosystem. It also gave me an opportunity to build something non-trivial using machine learning techniques, and my background in games made an interactive demo a good fit.

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Heading into PyCon, we wanted to put together something to demonstrate some of the excellent Python packages that are available in the machine learning space as well as showing off some of the newly integrated Intel® Math Kernel Library (MKL) optimizations in the latest ActivePython release. That demo became “NeuroBlast”, a classic arcade space shooter game that features enemies powered by machine learning. It was a fun way to get folks engaged at our booth and to learn about what’s available in the incredible Python ecosystem. It also gave me an opportunity to build something non-trivial using machine learning techniques, and my background in games made an interactive demo a good fit.

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Heading into PyCon, we wanted to put together something to demonstrate some of the excellent Python packages that are available in the machine learning space as well as showing off some of the newly integrated Intel® Math Kernel Library (MKL) optimizations in the latest ActivePython release. That demo became “NeuroBlast”, a classic arcade space shooter game that features enemies powered by machine learning. It was a fun way to get folks engaged at our booth and to learn about what’s available in the incredible Python ecosystem. It also gave me an opportunity to build something non-trivial using machine learning techniques, and my background in games made an interactive demo a good fit.

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Heading into PyCon, we wanted to put together something to demonstrate some of the excellent Python packages that are available in the machine learning space as well as showing off some of the newly integrated Intel® Math Kernel Library (MKL) optimizations in the latest ActivePython release. That demo became “NeuroBlast”, a classic arcade space shooter game that features enemies powered by machine learning. It was a fun way to get folks engaged at our booth and to learn about what’s available in the incredible Python ecosystem. It also gave me an opportunity to build something non-trivial using machine learning techniques, and my background in games made an interactive demo a good fit.
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Many organizations stopped upgrading Perl after the release of 5.8.8 or 5.10.1, about 8 to 11 years ago. At that point in history, major releases of Perl could take many years to come to fruition. To make things more confusing, point releases of a given version sometimes contained large changes (including backwards incompatibilities) that we'd expect in major releases. For example, 5.10.1, released 20 months after 5.10, contained a number of backwards incompatibilities and quite a few new features.

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Many organizations stopped upgrading Perl after the release of 5.8.8 or 5.10.1, about 8 to 11 years ago. At that point in history, major releases of Perl could take many years to come to fruition. To make things more confusing, point releases of a given version sometimes contained large changes (including backwards incompatibilities) that we'd expect in major releases. For example, 5.10.1, released 20 months after 5.10, contained a number of backwards incompatibilities and quite a few new features.
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In this release, we've focused on bringing the difficult to build data science packages to all ActivePython users on Windows, MacOS, and Linux. In particular, this release features machine learning, data engineering, data science collaboration, and an increased focus on providing the strongest security packages available in the ecosystem. As the saying goes...but wait, there's more! Since machine learning requires serious performance, we’ve added some outstanding enhancements thanks to the performance experts at Intel.

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In this release, we've focused on bringing the difficult to build data science packages to all ActivePython users on Windows, MacOS, and Linux. In particular, this release features machine learning, data engineering, data science collaboration, and an increased focus on providing the strongest security packages available in the ecosystem. As the saying goes...but wait, there's more! Since machine learning requires serious performance, we’ve added some outstanding enhancements thanks to the performance experts at Intel.
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