algorithms

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Published By: Coyote Point Systems     Published Date: Sep 02, 2010
The idea of load balancing is well defined in the IT world: A network device accepts traffic on behalf ofa group of servers, and distributes that traffic according to load balancing algorithms and the availabilityof the services that the servers provide. From network administrators to server administrators to applicationdevelopers, this is a generally well understood concept.
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coyote point, adc, buyer's guide, web applications, server load, server hardware, networking, virtualized network
    
Coyote Point Systems
Published By: HERE Technologies     Published Date: Apr 04, 2019
Artificial Intelligence (AI) has already begun to improve targeting, segmentation, media buying and planning in the advertising industry. AI algorithms can extract complex patterns from vast numbers of data points, and in so doing, are able to self-correct and learn patterns. The revenue potential that improved personalization, segmentation and targeting that AI provides to marketers is huge. At HERE Technologies, we are placing AI and machine learning at the center of our products and services. We see the opportunity in automated machine learning to enrich the targeting and effectiveness of mobile advertising campaigns in real time. But the outcome of implementing such technology depends on the quality of data being fed into it from the outset. AI wouldn’t be as helpful if it’s being used alongside questionable location data or audience data. HERE’s location data provides a strong thread that can be woven throughout every stage of the media buying process, offering more context and
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location data, ad tech, location targeting
    
HERE Technologies
Published By: F5 Networks Inc     Published Date: Dec 08, 2017
The NSA’s Information Assurance Directorate left many people scratching their heads in the winter of 2015. The directive instructed those that follow its guidelines to postpone moving from RSA cryptography to elliptic curve cryptography (ECC) if they hadn’t already done so. “For those partners and vendors that have not yet made the transition to Suite B elliptic curve algorithms, we recommend not making a significant expenditure to do so at this point but instead to prepare for the upcoming quantum-resistant algorithm transition.” The timing of the announcement was curious. Many in the crypto community wondered if there had been a quantum computing breakthrough significant enough to warrant the NSA’s concern. A likely candidate for such a breakthrough came from the University of New South Wales, Australia, where researchers announced that they’d achieved quantum effects in silicon, which would be a massive jump forward for quantum computing.
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quantum computing, quantum, computing, browser encryption. encryptionm
    
F5 Networks Inc
Published By: Oracle     Published Date: Dec 21, 2018
The transition to autonomous is all around. Its capability for problem-solving has never been seen before. Its potential for creating business value from algorithms and data makes it the next big frontier for business leaders. Two industry experts have discussed Oracle Autonomous Data Warehouse Cloudand what it can help organisations achieve. Talking about innovation, security and efficiency, they put the casefor an autonomous future.
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Oracle
Published By: Dell EMC     Published Date: Feb 14, 2019
Isilon scale-out NAS delivers the analytics performance and extreme concurrency at scale to feed the most data hungry analytic algorithms. Access this overview from Dell and Intel® to learn more. Intel Inside®. Powerful Productivity Outside.
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Dell EMC
Published By: FusionOps     Published Date: Jun 15, 2016
The supply chain generates huge volumes of data captured in ERP, CRM, demand planning and other systems. Download this whitepaper to learn how FusionOps Machine Learning can provide companies with a more accurate, granular understanding of their business by harmonizing these disparate data sources in the cloud, and applying machine learning algorithms.
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FusionOps
Published By: Dell PC Lifecycle     Published Date: Mar 09, 2018
Compression algorithms reduce the number of bits needed to represent a set of data—the higher the compression ratio, the more space this particular data reduction technique saves. During our OLTP test, the Unity array achieved a compression ratio of 3.2-to-1 on the database volumes, whereas the 3PAR array averaged a 1.3-to-1 ratio. In our data mart loading test, the 3PAR achieved a ratio of 1.4-to-1 on the database volumes, whereas the Unity array got 1.3 to 1.
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Dell PC Lifecycle
Published By: Akamai     Published Date: Jun 04, 2010
Predictive analytics have been used by different industries for years to solve difficult problems that range from detecting credit card fraud to determining patient risk levels for medical conditions. It combines data mining and machine-learning technologies to create statistical models based on historical data. It then uses these models to predict future events. Extracting the power from the data requires powerful algorithms behind predictive analytics.
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akamai, predictive, online advertising, tracking pixels, online shopping, in-market, site visitors, performance marketing
    
Akamai
Published By: Clustrix     Published Date: Sep 04, 2013
Find out how AdScience has been able to increase their revenue potential by five times using Clustrix to optimize bidding for their online ad broker agency. AdScience runs complicated algorithms to process bids for ad space based on click history. It's critical for AdScience to have instant access to smart data.
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adscience, revenue, technology, clustrix, algorithms, case study, best practices, networking
    
Clustrix
Published By: CA Technologies EMEA     Published Date: Sep 14, 2018
The misuse or takeover of privileged accounts constitutes the most common source of breaches today. CA Threat Analytics for PAM provides a continuous, intelligent monitoring capability that helps enterprises detect and stop hackers and malicious insiders before they cause damage. The software integrates a powerful set of user behavior analytics and machine learning algorithms with the trusted controls provided by CA Privileged Access Manager (CA PAM). The result is a solution that continuously analyzes the activity of individual users, accurately detects malicious and high-risk activities and automatically triggers mitigating controls to limit damage to the enterprise.
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CA Technologies EMEA
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: Monetate     Published Date: Oct 11, 2018
Monetate Intelligent Recommendations is the only solution that gives merchandisers & digital marketers the power to show contextually relevant product recommendations without burdening IT resources. Using manually curated or algorithmically-driven recommendations, marketers can easily support even the most complex product catalogs. Our solution filters recommendations based on customer attributes (e.g. shirt size), longitudinal behaviours (e.g. browsing behaviour), and situational context (e.g. product inventory at local stores). Best of all, an orchestration layer intelligently selects which algorithms and which filters to apply in any given situation, for any particular individual.
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Monetate
Published By: Monetate     Published Date: Oct 22, 2018
Monetate Intelligent Recommendations automates recommendations at scale without sacrificing any of the control you require. Our proprietary algorithms know what to serve each individual shopper to maximise brand value, while still allowing the control of an unlimited number of business guardrails defined by you.
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monetate, intelligent, recommendations, business, individual, automation
    
Monetate
Published By: HERE Technologies     Published Date: Mar 06, 2019
On-demand companies rely on fast, accurate and robust mapping and location technologies to provide their users with a superior experience. Find out how real-time, predictive and historical traffic data can be applied to traffic-enabled routing algorithms to influence route calculations and automatically plot multiple routes with waypoints sequencing. Discover how HERE can help you communicate updated ETAs and provide an optimized experience to your drivers and customers.
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location data, transport & logistics, location services
    
HERE Technologies
Published By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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ibm, big data, inline analytics, business analytics, roi
    
IBM
Published By: CA Technologies EMEA     Published Date: Aug 07, 2017
Generate rich virtual data that covers the full range of possible scenarios and provide the unconstrained access to environments needed to deliver rigorously tested applications on time and within budget. Model complex live system data and apply automated rule-learning algorithms to pay off technical debt and uncover in depth understanding of composite applications, while exposing virtual data to distributed teams on demand and avoiding testing bottlenecks.
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virtual services, data, avoid project delays, ca technologies, continuous testing, testing effort, service virtualisation, delivery ecosystem
    
CA Technologies EMEA
Published By: IBM APAC     Published Date: May 14, 2019
Machine Learning For Dummies, IBM Limited Edition, gives you insights into what machine learning is all about and how it can impact the way you can weaponize data to gain unimaginable insights. Your data is only as good as what you do with it and how you manage it. In this book, you discover types of machine learning techniques, models, and algorithms that can help achieve results for your company. This information helps both business and technical leaders learn how to apply machine learning to anticipate and predict the future. You will find topics like: - What is machine learning? - Explaining the business imperative - The key machine learning algorithms - Skills for your data science team - How businesses are using machine learning - The future of machine learning
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IBM APAC
Published By: Here Technologies     Published Date: Apr 01, 2019
On-demand companies rely on fast, accurate and robust mapping and location technologies to provide their users with a superior experience. Find out how real-time, predictive and historical traffic data can be applied to traffic-enabled routing algorithms to influence route calculations and automatically plot multiple routes with waypoints sequencing. Discover how HERE can help you communicate updated ETAs and provide an optimized experience to your drivers and customers.
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location data, transport & logistics, location services
    
Here Technologies
Published By: Oracle     Published Date: Mar 01, 2019
The transition to autonomous is all around. Its capability for problem-solving has never been seen before. Its potential for creating business value from algorithms and data makes it the next big frontier for business leaders. Two industry experts have discussed Oracle Autonomous Data Warehouse Cloud and what it can help organisations achieve. Talking about innovation,security and efficiency, they put the case for an autonomous future. Watch the webinar.
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Oracle
Published By: MobileIron     Published Date: Aug 20, 2018
MobileIron knows that cybercriminals are continuously generating more advanced ways to steal your data by any means necessary. That’s why we are committed to continually innovating and delivering new solutions that help our customers win the race against time to get ahead of the latest mobile security threats. As part of that commitment, MobileIron Threat Defense supports the five critical steps to deploying advanced, on-device mobile security. Our solution provides a single, integrated app that delivers several key advantages: • A single app of threat protection is fully integrated with EMM. • No user action is required to activate or update on-device security. • Advanced mobile security blocks known and zero-day threats across iOS and Android devices with no Internet connectivity required. • Machine-learning algorithms instantly detect and remediate on-device DNA threats.
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mobile, threat, defense, strategy, mobileiron, innovation
    
MobileIron
Published By: TIBCO Software     Published Date: Jul 22, 2019
Over the past decade there has been a major transformation in the manufacturing industry. Data has enabled a paradigm shift, with real-time IoT sensor data and machine learning algorithms delivering new insights for process and product optimization. Smart Manufacturing, also known as Industry 4.0, has laid the groundwork for the next industrial revolution. Using a smart factory system, all relevant data is aggregated, analyzed, and acted upon. We call this Manufacturing Intelligence, which gives decision-makers a competitive edge to: Digitize the business Optimize costs Accelerate innovation Survive digital disruption Watch this webinar to understand use cases and their underlying technology that helped our customers become smart manufacturers.
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TIBCO Software
Published By: Amazon Web Services     Published Date: Feb 01, 2018
At Amazon, we’ve been investing deeply in AI for more than 20 years. Machine learning (ML) algorithms drive many of our internal systems, and have formed the core of our customers' experience —from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, and our new retail experience, Amazon Go. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every executive, developer, and data scientist.
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machine learning, algorithms, interal systems, amazon
    
Amazon Web Services
Published By: Reputation.com     Published Date: Feb 26, 2018
In 2017, review sources proliferated, consumers became more savvy about the validity of online reviews, and the position of Chief Experience Officer started to gain traction among locationbased organizations. ORM and SEO became increasingly intertwined as Google refined its search algorithms with a strong emphasis on reviews and star ratings.
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Reputation.com
Published By: TIBCO Software     Published Date: Feb 27, 2019
Blockchain in Financial Services is receiving a lot of attention, especially for synchronizing financial agreements between institutions. But how can blockchain be used outside of this context? Can it apply to use cases such as identity, fraud, and AML? Watch this short webinar to hear how blockchain can be used to solve other key issues facing the industry, about research into consensus algorithms beyond proof of work, and about myths and truths that must be considered for a successful enterprise blockchain implementation. Speaker: Nelson Petracek, CTO, TIBCO Software
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blockchain, financial services, fraud, aml
    
TIBCO Software
Published By: TIBCO Software     Published Date: Feb 26, 2019
MoneyLIVE’s annual survey of over 600 banking professionals found that traditional banks face a significant challenge when it comes to building AI-powered customer journeys. 75% believe that as the use of AI intensifies, banks will struggle to recruit the necessary expertise. 84% fear regulatory and liability issues surrounding AI. Just 7% think their organization’s use of AI is highly sophisticated. But for banks to keep pace with challengers and FinTechs, it’s crucial that they harness this continually evolving technology. Download this chapter of MoneyLIVE's The Future of Retail Banking Report 2018/19 now and understand how TIBCO’s Connected Intelligence Platform, with the use of AI and machine learning algorithms, can help with banks’ digital transformation needs.
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artificial intelligence, machine learning, financial services, retail banking
    
TIBCO Software
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