machine learning

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Algorithmic Insurance Using Machine Learning and Artificial Intelligence to Make Better Decisions

Published By: TIBCO Software     Published Date: Jul 22, 2019
The Insurance industry continues to undergo significant transformation, with new technologies, business models, and competitors entering the market at an increasing rate. To be successful in attracting and retaining the most valuable customers, insurance companies must innovate and increase the speed at which they respond to customer demands. Traditionally, the insurance software market was dominated by a handful of specialist vendors with products that were initially expensive, difficult to deploy, costly to maintain, and did not provide the speed needed for today’s market. Now there has been a shift away from these “black box” applications to platforms that allow insurers to make their algorithmic IP available to business users, allowing much faster response to business demands. The algorithmic platform approach also comes at a fraction of the cost of black box solutions, while delivering advanced analytical techniques like Machine Learning and Artificial Intelligence (AI).
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TIBCO Software

Manufacturing Intelligence: Keep Your Processes Under Control

Published By: TIBCO Software     Published Date: Jul 22, 2019
On-demand Webinar The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and the need to rework faulty products. Watch this webinar to learn how TIBCO’s Smart Manufacturing solutions can help you overcome these challenges. You will also see a demonstration of TIBCO technology in action around improving yield and optimizing processes while also saving costs. What You Will Learn: Applying advanced analytics & machine learning / AI techniques to optimize complex manufacturing processes How multi-variate statistical process control can help to detect deviations from a baseline How to monitor in real time the OEE and produce a 360 view of your factory The webinar also highlights customer case studies from our clients who have already successfully implemented process optimization models. Spe
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TIBCO Software

Bloor InDetail: IBM Cloud Private for Data

Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
IBM Cloud Private for Data is an integrated data science, data engineering and app building platform built on top of IBM Cloud Private (ICP). The latter is intended to a) provide all the benefits of cloud computing but inside your firewall and b) provide a stepping-stone, should you want one, to broader (public) cloud deployments. Further, ICP has a micro-services architecture, which has additional benefits, which we will discuss. Going beyond this, ICP for Data itself is intended to provide an environment that will make it easier to implement datadriven processes and operations and, more particularly, to support both the development of AI and machine learning capabilities, and their deployment. This last point is important because there can easily be a disconnect Executive summary between data scientists (who often work for business departments) and the people (usually IT) who need to operationalise the work of those data scientists
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Group M_IBM Q2'19

The Forrester Wave™: Machine Learning DataCatalogs, Q2 2018

Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
In our 29-criteria evaluation of machine learning data catalogs (MLDCs) providers, we identified the 12 most significant ones — Alation, Cambridge Semantics, Cloudera, Collibra, Hortonworks, IBM, Infogix, Informatica, Oracle, Reltio, Unifi Software, and Waterline Data — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) professionals make the right choice.
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Group M_IBM Q2'19

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

DataRobot Automated Machine Learning Platform

Published By: Datarobot     Published Date: May 14, 2018
The DataRobot automated machine learning platform captures the knowledge, experience, and best practices of the world’s leading data scientists to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods
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Datarobot

Automated Machine Learning on AWS with DataRobot

Published By: Datarobot     Published Date: May 14, 2018
Organizations across industries look to technology, not only as a way to run their operations more smoothly, but as a way to gain competitive advantage. Artificial Intelligence (AI) and machine learning have transformed the businesses that are aggressively adopting these technologies, allowing them to systematically solve business problems faster and more effectively.
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Datarobot

Hero Insight - Developing trust in your people data

Published By: Oracle     Published Date: Jun 04, 2019
In our recent report, we look into the reasons why HR feel less than confident in their ability to manage the volume of data securely and ethically. From extracting the right type of insights to improving employee productivity and engagement to managing the skills pipeline. We look forwards to how HR can improve their systems by using automated technologies such as artificial intelligence and machine learning. Read the survey today to see how your organisation compares to your peers.
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Oracle

How to do Deep Learning with SAS

Published By: SAS     Published Date: May 24, 2018
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. You’ll then be ready to experiment with these methods in SAS Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
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SAS

Five Steps to Better People Analytics

Published By: Workday     Published Date: Jan 09, 2019
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.
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Workday

Powerful Personalization

Published By: Adobe     Published Date: Oct 11, 2018
Adobe offers powerful personalization tools that help you give your customers custom experiences every time they interact with you. With Adobe, you can take control of your data, use AI to achieve scale, and see incredible results. Adobe Target helps marketers deliver relevant, personalized experiences to highly targeted audiences based on behavioral analytics and audience data. Powered by AI and machine learning, users can deliver individualized customer experiences at massive scale.
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Adobe

Mobile Threat Detection Through Machine Learning

Published By: MobileIron     Published Date: Feb 12, 2019
The types of threats targeting enterprises are vastly different than they were just a couple of decades ago. This paper examines some current mobile threat defense approaches to help organizations understand where traditional solutions may fall short — and how machine learning-based threat defense can expand upon those capabilities by providing immediate, on-device protection against mobile attacks.
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MobileIron

Deliver Chatbots That Propel Your AI Strategy

Published By: Oracle     Published Date: Feb 21, 2018
A basic chatbot isn’t that hard to build. In JavaScript, write a public REST endpoint to connect a Facebook page to some chat logic (botly is a popular option) and deploy the whole thing to run on a cloud platform. Zoom out to the bigger picture, though, and you see that Facebook is just one channel. If you use Skype, Slack, Kik, and digital voice assistants, you’ll have to build six or eight of these endpoints straight away. And chatbots are being asked to handle ever more complex responses, so you better build on a platform of machine learning and natural language processing to keep up. That’s why the question enterprise developers should be asking is not “Which chatbot service do I start with?” but “Which platform will let me crank out a chatbot today and also support multiple channels and integrate with back-end systems as these chatbots take off?”
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Oracle

5 Trend Tecnologici Che Ridefiniscono la Customer Experience

Published By: Genesys     Published Date: Feb 12, 2019
Abbiamo chiesto a una serie di analisti e figure di riferimento del settore di indicarci quali saranno secondo loro le tendenze chiave relative all’engagement del cliente a partire dal 2017. Da tecnologie all’avanguardia come l’IoT e i Bot fino a nuove interpretazioni di idee del passato, i temi caldi indicati hanno fatto emergere cinque trend fondamentali destinati a ridefinire il futuro della Customer Experience. In questo ebook, scoprirai: I cinque trend che avranno il maggiore impatto sulla Customer Experience Come usare il machine learning per identificare tendenze e modelli utili a offrire un’eccezionale Customer Experience di nuova generazione Come avere un contact center all’avanguardia e adattarlo alle esigenze in rapida evoluzione dei clienti
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Genesys

Six Reasons to Switch to Juniper Networks Unite Cloud-Enabled Enterprise

Published By: Juniper Networks     Published Date: Aug 08, 2017
As enterprises embark on the digital transformation to take advantage of artificial intelligence, big data, machine learning, IoT, and cloud, they need a network infrastructure that gives them a solid foundation. Juniper Networks® Unite CloudEnabled Enterprise allows networking across your entire enterprise—campus, branch, and data center—ultimately helping you reduce risk, increase agility, lower costs, and enhance the customer experience. Here are the Top 6 reasons why enterprises embarking on the journey of digital transformation should switch to the Juniper Unite Cloud-Enabled Enterprise solution.
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Juniper Networks

MIT Technology Review Insights Report: Anticipating Cloud Work’s Most Common Side Effects

Published 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

Harnessing the Rising Tide of Data to Make Business Impact

Published 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.

CIO’s Guide to Data Analytics and Machine Learning

Published By: Google Cloud     Published Date: Feb 22, 2018
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Google Cloud

Machine Learning: The New Proving Ground for Competitive Advantage

Published By: Google Cloud     Published Date: Feb 22, 2018
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Google Cloud

Meet the new competitive differentiator: machine learning

Published By: Google Cloud     Published Date: Feb 22, 2018
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Google Cloud

Need help getting started with machine learning? Your guide is here

Published By: Google Cloud     Published Date: Feb 22, 2018
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Google Cloud

To the Cloud and Beyond: Big Data in the Age of Machine Learning

Published By: Google Cloud     Published Date: May 09, 2018
To the Cloud and Beyond: Big Data in the Age of Machine Learning
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Google Cloud

Lessons in Machine Learning Early Adopters Share their Strategies

Published By: Google Cloud     Published Date: May 09, 2018
LESSONS IN MACHINE LEARNING: EARLY ADOPTERS SHARE THEIR STRATEGIES
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Google Cloud
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