machine learning

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By: Revolution Analytics     Published Date: May 09, 2014
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. Through techniques of supervised and unsupervised statistical learning, organizations can make important predictions and discover previously unknown knowledge to provide actionable business intelligence. In this guide, we’ll examine the principles underlying machine learning based on the R statistical environment. We’ll explore machine learning with R from the open source R perspective as well as the more robust commercial perspective using Revolution Analytics Enterprise (RRE) for big data deployments.
Tags : revolution analytics, data science, big data, machine learning
     Revolution Analytics
By: Citrix ShareFile     Published Date: Jul 02, 2019
Get the report to find out how smart organizations are using new strategies to simplify IT infrastructures and empower employees to do their best work: • Get advice from Google and Citrix on how to manage the cloud transition strategically • Avoid common cloud work side effects such as excessive application logins, siloed data searches, and channel switching • Capture a vision for how artificial intelligence (AI) and machine learning are making work even more intuitive and personalized
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     Citrix ShareFile
By: HP Inc.     Published Date: Jun 20, 2019
Four billion people now generate four quintillion bytes of data every day - and with the number of IoT devices set to increase to three times the global population by 2022 - volumes will only continue to rise. The challenge is processing the data. This is why machine learning, deep learning and all the other developing forms of AI must deliver the analytics toolset businesses need to compete.
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     HP Inc.
By: AWS     Published Date: Jun 24, 2019
Join our webinar to hear how Consensus, a Target-owned subsidiary, utilizes AWS and Trifacta to prepare data for use in fraud detection algorithms. You’ll learn how self-service automated data wrangling can save your organization time and money, and tips for getting started with Trifacta’s solution, built for AWS. Webinar attendees will learn: Why automating your data wrangling tasks can lead to greater data accuracy and more meaningful insights. How you can reduce your data preparation time by 60% and more with self-service data wrangling tools built for AWS. How easy it is to get started with machine learning solutions for data wrangling on the cloud.
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     AWS
By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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     Cisco
By: Entrust Datacard     Published Date: Mar 20, 2017
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
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     Entrust Datacard
By: Hewlett Packard Enterprise     Published Date: Jun 17, 2019
"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond the remote monitoring systems of a prior generation. Three key features differentiate cloud-based predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically what types of value these systems can drive, IDC discusses them at some length in this white paper."
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
The bar for success is rising in higher education.  University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
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     Hewlett Packard Enterprise
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
Tags : location data, ad tech, location targeting
     HERE Technologies
By: Cisco EMEA     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Tags : big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
     Cisco EMEA
By: Box     Published Date: Jun 22, 2018
• Facing a myriad of challenges from digital transformation, business today are making big bets on the best collaboration tools they need on hand to meet those challenges. From employee buy-in, to machine-learning capabilities, to security, it's important to select a service with the right capabilities to further your business goals. The challenge, however, is that with so many services to choose from it can be difficult to figure out which one is the right fit for your business. • This eBook, 5 Considerations in Choosing a Collaboration Platform in the Digital Age, will walk you through the ins and outs of what to keep in mind as you choose the best collaboration platform for you.
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     Box
By: Hewlett Packard Enterprise     Published Date: May 10, 2019
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates. ? Optimal application performance and delivery is difficult to achieve in complex environments. ? Many IT infrastructure and operations teams are stretched to the breaking point. ? Predictive analytics and machine learning can be applied to great effect
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Mar 26, 2018
Business users expect immediate access to data, all the time and without interruption. But reality does not always meet expectations. IT leaders must constantly perform intricate forensic work to unravel the maze of issues that impact data delivery to applications. This performance gap between the data and the application creates a bottleneck that impacts productivity and ultimately damages a business’ ability to operate effectively. We term this the “app-data gap.”
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Jul 19, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: Top 5 causes of downtime and poor performance across the infrastructure stack How machine learning and predictive analytics can prevent issues Steps you can take to boost performance and availability"
Tags : cloud, nimble storage, infrastructure
     Hewlett Packard Enterprise
By: Oracle     Published Date: Jan 16, 2018
Download this webinar to learn about Machine Learning and how it can be applied to finance, and acquire basic fundamentals about how to begin the journey.
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     Oracle
By: Dell EMC     Published Date: Oct 13, 2016
Flexibility is important, since many future initiatives—big data, machine learning, emerging technologies, and new business directions—will be built on this cloud structure. No matter what shape your cloud infrastructure takes, Dell EMC converged and hyper-converged platforms and innovations like Dell EMC VscaleTM Architecture, powered by Intel® Xeon® processors, deliver the pathways to scale-up and scale-out, today and tomorrow.
Tags : emc, capex, opex, roi, hyper-converged platforms
     Dell EMC
By: Genesys     Published Date: Jun 06, 2017
In this ebook, learn: - Five trends will have the biggest impact on customer experience - How to use machine learning to detect patterns and trends to deliver the next great customer experiences - How to future-proof your contact center and adapt to changing customer needs
Tags : genesys, customer experience, contact center solutions, contact center, customer needs
     Genesys
By: Hewlett Packard Enterprise     Published Date: Sep 25, 2017
Infographic based on the InfoSight report.
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Sep 25, 2017
Every week InfoSight analyzes more than a trillion data points from more than 9,000 customers. How does this translate into true business value? By reducing your business risk with over Six-Nines of measured availability. By providing you with an infrastructure that gets “smarter” every single day. By empowering IT staff to focus on business priorities instead of mundane maintenance.
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     Hewlett Packard Enterprise
By: SAS     Published Date: Jan 17, 2018
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally. Learn more about key findings, including: Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics. Return on investment for analytics stems from the governing and sharing of data throughout the organization. Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
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     SAS
By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
Tags : pentaho, analytics, platforms, hadoop, big data, predictive analytics, data science
     Pentaho
By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i
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     Oracle
By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect.
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: -Top 5 causes of downtime and poor performance across the infrastructure stack -How machine learning and predictive analytics can prevent issues -Steps you can take to boost performance and availability
Tags : 
     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Storage is normally the first suspect when identifying the causes of the App-Data Gap, but the facts tell a different story. Flash Alone Isn’t Enough. Infrastructure complexity makes it difficult to pinpoint the real problem, resulting in: • Extended downtime and frustration • Inefficient use of IT resources and budget • Long hours spent resolving cross-vendor issues
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     Hewlett Packard Enterprise
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