machine learning

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Machine Learning on AWS

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

Machine Learning in Business

Published By: Amazon Web Services     Published Date: Feb 01, 2018
Machine learning is proving its power across virtually every industry in ways that add actionable insight and efficiency. But one can look at the rise of this transformative paradigm with a more focused lens to see AI technologies as a business tool of the highest order, one that improves processes and inspires new models. AI, in other words, has a big role to play on the balance sheet. Two leading brands in very different spaces — Capital One in financial services, John Deere in agriculture — are seeing efforts that stretch back decades come to fruition with the launch of cloud-based AI platforms. Capital One is developing digital products and experiences using machine learning to help millions of customers with their financial lives; John Deere’s Precision Agriculture solution helps farmers gain precise information about their machines and crops. In both instances, AI and a cloud platform combine to enable transformation.
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digital, technologies, optimization, amazon
    
Amazon Web Services

Thinking Outside The Big Data Box: What Can Machine Learning Do For You?

Published By: Amazon Web Services     Published Date: Feb 01, 2018
Moving Beyond Traditional Decision Support Future-proofing a business has never been more challenging. Customer preferences turn on a dime, and their expectations for service and support continue to rise. At the same time, the data lifeblood that flows through a typical organization is more vast, diverse, and complex than ever before. More companies today are looking to expand beyond traditional means of decision support, and are exploring how AI can help them find and manage the “unknown unknowns” in our fast-paced business environment.
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predictive, analytics, data lake, infrastructure, natural language processing, amazon
    
Amazon Web Services

Gartner: Access the New Gartner Market Guide!

Published By: SessionM     Published Date: Jan 24, 2018
Download Gartner’s latest Market Guide for Master Data Management of Customer Data Solutions to learn market definition, analysis and recommendations, the criteria necessary for evaluating marketing data management solutions and how master data sits in the middle of the 360° customer view.
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customer engagement, unified customer profile, customer data platform, data orchestration, customer data activation, machine learning, data integration, personalization, cross-channel campaign management, single customer view, 360 profile, customer retention, customer loyalty, customer lifetime value, closed loop offers, next best offer, loyalty automation, loyalty platform, customer data management, customer data platform
    
SessionM

Analytics as a Source of Business Innovation

Published 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

How Machine Learning Will Transform Finance at Every Level

Published 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

2018 Outlook: Customer Experience and Security Strike a Balance

Published 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
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2018 trends, aml trends, money laundering trends
    
Fiserv

Accelerate Deep Learning With A Modern Data Platform

Published By: Pure Storage     Published Date: Jan 12, 2018
Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions. Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.
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reporting, artificial intelligence, insights, organization, institution, recognition
    
Pure Storage

O'Reilly's Deep learning: A Practitioner's Approach

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

CIO's Guide to Data Analytics & Machine Learning

Published By: Google     Published Date: Jan 08, 2018
Today’s smart computers can beat board game champions, master video games, and learn to recognize cats. No wonder artificial intelligence has captured the imaginations of business and IT leaders. And indeed, AI is starting to transform processes in established industries, from retail to financial services to manufacturing. Read this guide from Google Cloud and learn how you can unlock the transformational power of information and get useful insights from a vast and complex landscape of data.
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data analytics, machine learning, big data, artificial intelligence
    
Google

Magic Quadrant for Operational Database Management Systems

Published By: MarkLogic     Published Date: Nov 30, 2017
The OPDBMS market in 2017 brings cloud and fully managed options center stage for execution. Market-defining vision includes features for machine learning, serverless scenarios and streaming integration. Data and analytics leaders must balance current and future needs against this market landscape.
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MarkLogic

Advanced Analytics and Machine Learning: A Prescriptive and Proactive Approach to Security

Published By: McAfee EMEA     Published Date: Nov 15, 2017
Machine learning offers the depth, creative problem-solving capabilities, and automation to help security organizations gain significant ground against attackers. It’s a powerful tool for processing massive amounts of data for the purpose of malware classification and analysis, especially for unknown threats. Through supervised learning, human researchers can continually develop new training models that expand the understanding and competency of machine learning systems.
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analytics, security, problem solving, creative, data, researching, malware
    
McAfee EMEA

The Path to Predictive Analytics and Machine Learning

Published By: MemSQL     Published Date: Nov 15, 2017
The Path to Predictive Analytics and Machine Learning This Ebook will be your guide to building and deploying scalable, production-ready machine-learning applications. Inside, you will find several machine learning use cases, code samples to help you get started, and recommended data processing architectures.
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data pipelines, analytics, database, machine learning
    
MemSQL

Big Data & Analytics for Dummies

Published 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.
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big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
    
Cisco EMEA

Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime

Published 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.
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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

IoT está habilitando una nueva era de valor para los accionistas en las empresas de energía y recurs

Published 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).
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SAP SME

Accelerate Business Agility with Faster Server Refresh Cycles

Published By: Dell and VMWare     Published Date: Oct 26, 2017
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance.
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Dell and VMWare

Accelerate Business Agility with Faster Server Refresh Cycles

Published By: Dell and VMWare     Published Date: Oct 26, 2017
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance.
Tags : 
    
Dell and VMWare

Accelerate Business Agility with Faster Server Refresh Cycles

Published By: Dell and VMWare     Published Date: Oct 26, 2017
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance.
Tags : 
    
Dell and VMWare

Accelerate Business Agility with Faster Server Refresh Cycles

Published By: Dell and VMWare     Published Date: Oct 26, 2017
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance.
Tags : 
    
Dell and VMWare

Secure Platform for Scale-Out and Cloud Infrastructure

Published By: Oracle     Published Date: Oct 20, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most compani
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Oracle

Forrester Webcast: Deciphering Development Trends

Published 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

The Rise of the Renaissance Database Administrator

Published 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 is also a
Tags : 
    
Oracle

Secure Platform for Scale-Out and Cloud Infrastructure

Published By: Oracle CX     Published Date: Oct 19, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most companies
Tags : 
    
Oracle CX
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