machine learning

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Published By: TIBCO Software     Published Date: Jul 22, 2019
What if you could use just one platform to detect all types of major financial crimes? One platform to handle the analytical tasks of fraud detection, including: Data processing and aggregation Data visualization Statistical/mathematical/machine learning modeling Batch/real-time scoring One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud. Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
FINANCIAL SERVICES’ HISTORY OF DISRUPTION Financial Services is an industry driven by disruption. Transformative business models such as low-cost brokerages, innovative investment products like ETFs, and the huge regulatory mandates like Gramm-Leach-Bliley are but a few examples. Here are some others: • New fintech firms such as a recent nine billion dollar investment in Ant Financial Services Group and myriad other venture capital-led fintech startups targeting well established segments across the financial services industry • Robo-advisor services powered by artificial intelligence and machine learning intermediating financial advisors and portfolio managers alike • Ever changing regulatory and risk management mandates, such as GDPR, Basel III, and Open Banking, transforming customer engagement and capital allocation Read this whitepaper to learn how you can overcome these and other disruptions.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
TIBCO® Connected Intelligence for Smart Factory Insights By processing real-time data from machine sensors using artificial intelligence and machine learning, it's possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
Today, you can improve product quality and gain better control of the entire manufacturing chain with data virtualization, machine learning, and advanced data analytics. With all relevant data aggregated, analyzed, and acted on, sensors, devices, people, and processes become part of a connected Smart Factory ecosystem providing: •? Increased uptime, reduced downtime •? Minimized surplus and defects •? Better yields •? Reduced cost due to better quality •? Fewer deviations and less non-conformance
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TIBCO Software
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: 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
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
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
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
Published By: Group M_IBM Q3'19     Published Date: Aug 21, 2019
Artificial intelligence (AI), including machine learning and deep learning, is set to become one of the most transformational technologies in the history of the world, affecting most aspects of our lives whether we’re conscious of it or not. The application of these technologies will likely reshape how people work, study, travel, govern, consume and pursue leisure activities.
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Group M_IBM Q3'19
Published By: Acoustic     Published Date: Oct 04, 2019
Simply put: Marketing isn’t what it used to be. If you want to compete in this rapid digital world, you need to make your customers happy. Constantly. We’ll get you started with nine of the most exciting trends developing in the world of marketing in 2019. With this report, you’ll learn: How the new director of marketing data position and GDPR compliance can build customer trust. What it means for customer centricity now that MarTech and AdTech are finally coming together with AI and machine learning. How to adjust your business purpose to create customer loyalty as the attention economy shifts to the emotion economy.
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Acoustic
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
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
Published By: Oracle     Published Date: Sep 30, 2019
Do you want more powerful insights from your data? Are you looking for ways to make your data more secure? Hear how you can do this using technology, AI, machine learning, and automation in a secure, compliant, and sustainable way. In this episode of tomorrow talks with IDC and Oracle the conversation moves on from who’s responsible for data security to making sure data delivers value. To find out more download the webinar today.
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Oracle
Published By: Oracle     Published Date: Sep 09, 2019
Do you want more powerful insights from your data? Are you looking for ways to make your data more secure? Hear how you can do this using technology, AI, machine learning, and automation in a secure, compliant, and sustainable way. In this episode of tomorrow talks with IDC and Oracle the conversation moves on from who’s responsible for data security to making sure data delivers value. To find out more download the webinar today.
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Oracle
Published By: Oracle EMEA     Published Date: Oct 08, 2019
Data management doesn’t come easier than this. Thanks to machine learning, artificial intelligence and the power of the cloud just about anyone can gain insight of their data. Easy to install, just tell the service level what you want and it does the rest. Oracle Autonomous Database self-repairs, patches automatically and counters threats with artificial intelligence. Autonomous for Dummies? We think its pretty smart.
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Oracle EMEA
Published By: Oracle EMEA     Published Date: Dec 10, 2019
This webinar demonstrates how connected data changes everything. In an autonomous world you’ll take the lead, becoming central to your company’s success. Machine learning will take care of the day-to-day maintenance leaving you to focus on design, analytics and strategy. And crucially, you’ll find yourself empowering and inspiring your colleagues to gain their own insights from real- time data.
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Oracle EMEA
Published By: Oracle EMEA     Published Date: Feb 13, 2020
This webinar demonstrates how Autonomous Database benefits your whole organisation. It’s so easy to use – simply load and run. And there’s no need to be an expert, business colleagues with no machine learning experience can use Autonomous Database in an intuitive way. Your role is key in empowering them to gain insights and generate reports from real-time data.
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Oracle EMEA
Published By: Oracle EMEA     Published Date: Feb 13, 2020
Imagine your database taking care of itself with little or no administration by you. With Oracle Autonomous Database that’s exactly what you can look forward to. Thanks to machine learning, you can determine the service level you want and it does the rest. It will install patches automatically and use artificial intelligence to protect itself from threats. And while your operations are running, it constantly tunes itself to deliver 99.995 percent uptime.
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Oracle EMEA
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
Published By: MicroStrategy     Published Date: Nov 05, 2019
Organizations are embracing cloud-based solutions at an unprecedented rate. The transition to a cloud-first strategy is no longer viewed as a luxury but as a necessity for businesses to compete. According to a 2018 study, cloud computing will have the biggest impact on analytics initiatives, followed by big data, AI and machine learning, and IoT. Because today’s state-of-the-art solutions will likely be quickly outdated, organizations now want to invest in systems that can meet their changing needs. Attributes like flexibility and agility will allow these businesses to seamlessly tackle changing business requirements.
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MicroStrategy
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
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
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
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
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