machine learning

Results 126 - 150 of 351Sort Results By: Published Date | Title | Company Name
By: Workday     Published Date: Mar 02, 2018
Artificial intelligence (AI) and machine learning are redefining business analytics. But for HR, use cases can be much more complex. Learn five key steps to build a strong foundation for answering HCM questions today and position yourself to use AI in HR going forward.
Tags : artificial intelligence, hcm, five steps
     Workday
By: ClearStory     Published Date: Oct 07, 2014
Organizations are more data hungry than ever. Thanks to advances in machine learning and semantic processing, they can now gain new insights from that data. ClearStory Data helps business users gain new insights into their markets and the environments in which they operate.
Tags : data hungry, semantic processing, insight, market enviornment, data management, data center
     ClearStory
By: SAP SME     Published Date: Nov 02, 2017
La tecnología actual de IoT puede impulsar aún ás la innovación en las empresas de ENR. La disponibilidad de tecnología rentable basada en la nube, las analíticas y el machine learning ahora les permite a las empresas de ENR hacer mucho más con internet de las cosas (IoT).
Tags : 
     SAP SME
By: Juniper Networks     Published Date: Aug 07, 2017
Warum maschinelles Lernen entscheidend zur Cybersicherheit beiträgt
Tags : 
     Juniper Networks
By: Juniper Networks     Published Date: Aug 08, 2017
Pourquoi l’apprentissage automatique est essentiel pour la cybersécurité
Tags : 
     Juniper Networks
By: Google     Published Date: Aug 09, 2017
The business world’s focus on machine learning (ML) may seem like an overnight development, but the buzz around this technology has been steadily growing since the early days of big data.
Tags : machine learning, big data, analytics, data analytics
     Google
By: Fiserv     Published Date: Nov 09, 2017
Financial institutions seeking to attract new customers and revenue channels are expanding into digital services, real-time payments and global transactions. However, with every new service, criminals are developing innovative ways to infiltrate financial systems, and older technologies that mitigate fraud no longer work as effectively. So how can financial institutions respond to this growing threat? Fortunately, more advanced technologies hold great potential for real-time financial crime mitigation. Learn about five current and emerging technologies that could impact money laundering and fraud mitigation, including artificial intelligence/machine learning, blockchain, biometrics, predictive analytics (hybrid model) and APIs. Read the latest Fiserv white paper: Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime.
Tags : kyc, know your customer, beneficial ownership, financial crime, financial crimes, compliance, enhanced due diligence, suspicious activity report, currency transaction report, aml directive, anti-money laundering laws
     Fiserv
By: Fiserv     Published Date: Jan 16, 2018
For the past decade, financial institutions have created sophisticated digital platforms for consumers to access, save, share and interact with their financial accounts. As sophisticated as these digital platforms have become, cyber criminals continue to pose an ever-present risk for everyone – from individual consumers to large corporations In his recent article, 2018 Outlook: Customer Experience and Security Strike a Balance, Andrew Davies, vice president of global market strategy for Fiserv’s Financial Crime Risk Management division, explains how and why security will become a key differentiator for financial institutions as they respond to a changing landscape, which includes: •Global payment initiatives •Open Banking standards •Artificial intelligence and machine learning •Consumer demand for real-time fraud prevention and detection
Tags : 2018 trends, aml trends, money laundering trends
     Fiserv
By: Splunk     Published Date: Sep 10, 2018
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable. Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
Tags : it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
     Splunk
By: Splunk     Published Date: Nov 29, 2018
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences. Download the e-book to learn how: Micron Technology reduced number of IT incidents by more than 50% Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Tags : predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
     Splunk
By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
Tags : predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
     Splunk
By: Workday APAC     Published Date: May 08, 2019
As your organization’s finance leader, the opportunity to better understand the landscape and your business has never been greater. Advances in analytics—powered by digital technologies, such as automation and machine learning—give finance teams deeper business insights. Read the story.
Tags : 
     Workday APAC
By: Beqom     Published Date: Jun 14, 2019
New Techniques That Will Drive Revenue in 2019 If you’re ready to move beyond simple calculations and realize the vast potential of data driven selling, you’re ready to explore the next generation of SPM platforms. Download the report to learn how the modern technologies like Artificial Intelligence and Machine Learning, can give your sales reps a roadmap to better performance and give sales management insights that will enable them to achieve more profitable sales.
Tags : 
     Beqom
By: GFT USA, Inc.     Published Date: Jun 26, 2019
Stream is GFT’s architectural framework on GCP that enables real time processing and analysis of structured and unstructured data using AI and Machine Learning (ML) to extract intelligence from data.
Tags : 
     GFT USA, Inc.
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
Tags : 
     IBM APAC
By: Cisco     Published Date: Sep 27, 2018
As the world of traditional manufacturing fuses with information technology, organizations are tapping into a level of technical orchestration never attainable before. Symphonies of systems facilitate real - time interactions of people, machines, assets, systems, and things. This is the Smart Factory; the factory ecosystem of the future. It is an application of the Industrial Internet of Things (IIoT) built with sets of hardware and software that collectively enable processes to govern themselves through machine learning and cognitive computing
Tags : 
     Cisco
By: Infor     Published Date: Mar 03, 2017
Analysts and industry experts agree: Digital disruption in manufacturing is on the horizon. Technologies like the Internet of Things, dynamic enterprise management, global supply chain visibility, and machine learning are already changing the way manufacturers produce goods and interact with customers. Further changes will continue to intensify issues and reveal opportunities.
Tags : cio, finance, digital, manufacturing, enterprise, enterprise applications
     Infor
By: Infor     Published Date: Mar 03, 2017
Analysts and industry experts agree: Digital disruption in manufacturing is on the horizon. Technologies like the Internet of Things, dynamic enterprise management, global supply chain visibility, and machine learning are already changing the way manufacturers produce goods and interact with customers. Further changes will continue to intensify issues and reveal opportunities.
Tags : cfo, finance, digital, manufacturing, enterprise, enterprise applications
     Infor
By: Pure Storage     Published Date: Oct 09, 2018
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.
Tags : 
     Pure Storage
By: Nice Systems     Published Date: Feb 26, 2019
NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
Tags : 
     Nice Systems
By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
Tags : 
     Group M_IBM Q2'19
By: Oracle     Published Date: Mar 01, 2019
Join Oracle’s CX and Marketing Strategy Director, Wendy Hogan, and Senior Vice President Oracle Marketing, Shashi Seth, as they tell how AI, machine learning and data science can engage customers, automate tasks and build ROI. Reaching the right customers on the right channel at the right time, brings rewards for CMOs who embrace these innovations, including engaged customers and increased ROI. Be inspired by the new-generation AI, machine learning and data science and take your marketing to the next level. Watch the webinar.
Tags : 
     Oracle
By: Intel     Published Date: Apr 16, 2019
Gartner predicts that the public cloud market will surpass USD 300 billion by 2021 . With the big players (Amazon, Google, Microsoft and IBM) taking home 63 percent of the market share , how will next wave CSPs stand out from the crowd? Download Intel's latest whitepaper, Differentiating for Success: A Guide for Cloud Service Providers' to discover how to offer unique services, including: - Providing workload-specific optimizations, for example machine learning or high-performance computing - Targeting a particular geographical area - Focusing on an industry, such as financial services - Delivering emerging technology, such as virtual reality, in-memory databases, and containerization
Tags : 
     Intel
By: IBM APAC     Published Date: Aug 25, 2017
Machine learning automates the development of analytic models that can learn and make predictions on data. It has been one of the fastest growing disciplines within the world of statistics and data science, but the barrier to entry has been high, not only in cost, but also in the need for specialized talent.
Tags : machine learning, apache spark, additional resources, big data, ibm
     IBM APAC
By: KPMG     Published Date: Jul 10, 2018
As organisations increasingly leverage data, sophisticated analytics, robotics and AI in their operations, we ask who should be responsible for trusted analytics and what good governance looks like. Read this report to discover: • the four key anchors underpinning trust in analytics – and how to measure them • new risks emerging as the use of machine learning and AI increases • how to build governance of AI into core business processes • eight areas of essential controls for trusted data and analytics.
Tags : 
     KPMG
Start   Previous    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15    Next    End
Search White Papers      

Add White Papers

Get your white papers featured in the insideHPC White Paper Library contact: Kevin@insideHPC.com