mathematics

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Published By: Pure Storage     Published Date: Jan 12, 2018
Interest in machine learning has exploded over the past decade. You see machine learning in computer science programs, industry conferences, and the Wall Street Journal almost daily. For all the talk about machine learning, many conflate what it can do with what they wish it could do. Fundamentally, machine learning is using algorithms to extract information from raw data and represent it in some type of model. We use this model to infer things about other data we have not yet modeled. Neural networks are one type of model for machine learning; they have been around
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learning machines, automated intelligence, scalars, vectors, mathematics, classification, pure storage
    
Pure Storage
Published By: Fujitsu America, Inc.     Published Date: Jan 22, 2019
Teachers have always experimented with new technology and how it can be integrated to augment the lessons and content given to students. Classroom sets of books afforded teachers the opportunity to give homework, movie projectors and televisions offered an opportunity to display new content, and calculators transformed computational mathematics. Augmented and virtual reality are new tools that can transition pedagogy to include new materials and content. Students can travel to historical landmarks, world heritage sites, and past events from the safety of their classroom. Books can be scanned to reveal videos and three-dimensional content identified by the teacher to enhance the content available to the student. Download this whitepaper to learn more. Intel, the Intel logo, Intel Core, Intel vPro, Core Inside and vPro Inside are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.
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Fujitsu America, Inc.
Published By: Polycom     Published Date: Jul 24, 2014
Build or buy? When manufacturers have sought new leaders, they have typically done both: grooming talent in-house and paying market rates for the best thinkers and managers. With the growing STEM (science, technology, engineering, and mathematics) shortage, companies will be harder-pressed to buy – and keep – top technical talent. Emerging and established leaders will command premium prices and field continual offers, increasing the likelihood they’ll make frequent job changes, taking their industry and institutional knowledge with them. As a consequence, manufacturers will need to build their talent pipeline, empower knowledge workers with the tools and intelligence they need to succeed, and provide professional development opportunities that exceed what competitors offer. This will be a marathon, not a sprint. What’s key to making the race for talent successful: virtual training environments that accelerate learning and innovation.
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polycom, management, virtual, training, development, business technology
    
Polycom
Published By: GFI     Published Date: Jun 12, 2007
This white paper describes how Bayesian mathematics can be applied to the spam problem, resulting in an adaptive, 'statistical intelligence' technique that achieves very high spam detection rates.
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anti spam, anti-spam, filter, block, blocking, email security, phishing, baysian, bayesian, spam detection, gfi
    
GFI
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