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BigData News Wednesday, June 13

5 Open Source Libraries to Aid in Your Machine Learning Endeavors

  • Related:5 Strategies From Top Firms on How to Use Machine Learning – – While many factors have contributed to this increase in machine learning, one reason is that its becoming easier for developers to apply it, thanks to open source frameworks.
  • However, in most cases, framework refers to a bunch of programs, libraries andlanguages you have built to use in application development.
  • As one online user putit: The key difference between a library and a framework is ‘inversion of control.’
  • Amazon Machine Learning (AML) is built for developers, with many tools and wizards to help you create machine learning models without having to learn all the complexities of how machine learning works.
  • The list is extensive, but they include: SVMLight, LibSVM, libqp, SLEP, LibLinear, VowpalWabbitand NET machine learning framework, has multiple libraries to handle everything from pattern recognition, image and signal processing tolinear algebra, statistical data processing and more.

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5 Open Source Libraries to Aid in Your Machine Learning Endeavors

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  • Currently, Artificial Intelligence (AI) and Machine Learning are being used, not only as personal assistants for internet activities, but also to answer phones, drive vehicles, provide insights through Predictive and Prescriptive Analytics, and so much more.
  • The debate on the differences between Artificial Intelligence vs. Machine Learning are more about the particulars of use cases and implementations of the technologies, than actual real differences they are allied technologies that work together, with AI being the larger concept that Machine Learning is a part of.
  • Weak AI describes the status of most Artificial Intelligence entities currently in use, said Bowles, which is highly focused on specific tasks, and very limited in terms of responses.
  • That a corporation saves large amounts of money by using Artificial Intelligence, Machine Learning, and robotics, rather than people, is mentioned less often.
  • Artificial Intelligence (AI) came first, as a concept, withMachine Learning(ML), as a method for achieving Artificial Intelligence, emerging later.

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