machine learning

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Accelerate Deep Learning With A Modern Data Platform

Published By: Pure Storage     Published Date: Jul 03, 2019
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.
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Pure Storage

Accelerate Deep Learning with a Modern Data Platform

Published By: Pure Storage     Published Date: Apr 10, 2019
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
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Pure Storage

IT Strategies for AI Transformation

Published By: Pure Storage     Published Date: Apr 15, 2019
This year, businesses will increasingly turn to AI to power their business transformation. Machine learning and deep learning workloads are quickly becoming a mission-critical workload in the enterprise data center. As an IT leader, are you ready for the impending wave of AI applications that will demand new approaches to computing, storage and networking? Do you have the right strategy for scaling AI workload in your data center? We’ll introduce you to the IT visionaries who have made it happen. In this webinar we’ll explore how one IT leader accelerated his company’s success with an AI infrastructure strategy, sharing their best practices and insights. By watching this webinar, you'll learn: - Why it’s now critical for enterprise IT to have an AI infrastructure strategy that supports the business - Explore one IT leader’s experience developing and implementing a best-of-breed platform for scaling AI workload in the data center - Gain insights that can drive your AI infrastructur
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Pure Storage

Deep Learning Book

Published By: Pure Storage     Published Date: Dec 05, 2018
"Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures"
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Pure Storage

Accelerate Deep Learning with a Modern Data Platform

Published By: Pure Storage     Published Date: Dec 05, 2018
In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights for the massive amounts of data. Many organization are now using AI for leading-edge research or as a competitive advantage. This Datanami white paper not only covers the societal impacts of deep learning, but it also discusses why traditional storage can't meet deep learning needs and how having the right data hub can help deliver data throughput for AI.
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Pure Storage

Unlocking Customer Insights with Machine Learning

Published By: Q2 eBanking     Published Date: Jul 30, 2017
Many financial institutions see their customer data as one of their most valuable assets. Unlocking insights from that data helps FIs understand, anticipate and offer account holders the products and services they truly need. A major trend to unlocking customer insights is using machine learning to surface the behavioral intelligence buried in the large amount of account holder transactional data captured each and every day. In this paper, learn how a group of talented, enthusiastic analysts with an open approach to data can yield some very interesting and extremely valuable and actionable results. This approach, championed by Q2 Executive Vice President and CTO Adam Anderson, has led to a new platform, Q2 SMART, which provides powerful behavioral analytics for financial institutions, enabling growth while providing account holders with real value.
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Q2 eBanking

eBook : SAP on Azure

Published By: Rackspace     Published Date: May 28, 2019
Today, it isn’t a matter of if you’re taking SAP to the cloud – but a matter of when, and how you’re going to make it happen. Because by moving your SAP workloads to the cloud, you are putting them together with other data streams, advanced analytics and machine learning, to create a powerful combination to better engage customers, empower employees, optimize operations and transform products. This e-book introduces Rackspace as the managed cloud service provider to partner, for moving SAP workloads to Azure. Being certified in all the leading SAP technologies, including hosting services, HANA Operations and HANA Enterprise Cloud (HEC) – and having been awarded Microsoft Hosting Partner of the Year five times – Rackspace has got the whole SAP on Azure solution covered, from planning to deployment and ongoing management. Check out the case studies of global companies, like Rockwell Automation, The Mosaic Company, Malaysia Airlines and Coats & Clark, to discover how they have benefi
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Rackspace

The path to cloud-native applications

Published By: Red Hat     Published Date: Mar 28, 2019
Digital business brings to mind innovative technologies: mobile devices, intelligent sensors, wearable devices, virtual reality, chatbots, blockchain, machine learning, and other technology. For some, it also reflects the rapid rise of new digitally native businesses that have disrupted traditional business models and destabilized established companies and industry sectors. For the majority of organizations, digital business means pivoting to a culture of organizational agility, where the rapid pace of demand can only be satisfied by faster and more flexible development and delivery models. As most organizations do not have the luxury of completely rebuilding their technology foundation or immediately adopting new practices and mindsets, they are embracing gradual yet fundamental shifts in culture, processes, and technology to support greater velocity and agility.
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Red Hat

Forrester Wave: Machine Learning Data Catalogs

Published By: Reltio     Published Date: Nov 20, 2018
Big data is growing faster than the capabilities available to manage and analyze it. Get this vendor comparison to learn how a modern master data management platform will help you to achieve better outcomes.
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Reltio

Baldwin County Case Study

Published By: Rosetta Stone     Published Date: Aug 18, 2016
Baldwin County Public Schools has built a curriculum that includes preparing students for the world of intelligent machines and empowering them to participate in the global community through language acquisition. The district sought a technology-based solution to provide students with the opportunity for long-term language learning.
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Rosetta Stone

The Definitive Guide to Value Creation with Intelligent Cloud ERP

Published By: SAP     Published Date: Aug 22, 2018
Learn how Intelligent Cloud ERP empowers you to leverage the opportunities presented by changes to how we work, collaborate and achieve success in this practical, actionable overview.
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sap, cloud erp, intelligent erp, machine learning, collaboration, business management, enterprise resource planning, information management, cloud computing
    
SAP

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

Acelerar la transformación digital en la industria de los productos de consumo

Published By: SAP SME     Published Date: Apr 10, 2018
La industria de los productos de consumo está experimentando una gran transformación. Los consumidores demandan experiencias que ofrezcan confianza, alegía y protección – aunque son menos tangibles– estos son los impulsores que definirán el exito. Es por eso que las compañías de productos de consumo necesitan reimaginar todo, desde el compromiso del consumidor y las operaciones hasta la innovación de los productos. Las tecnologías emergentes como el Internet de las Cosas, Machine Learning e Inteligencia Artificial, pueden ayudar a guiar el rumbo de este cambio e impulsar el éxito del mismo.
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SAP SME

Statistics and Machine Learning at Scale

Published By: SAS     Published Date: Apr 20, 2015
This conclusions paper introduces key machine learning concepts and describes new SAS solutions – SAS In-Memory Statistics for Hadoop and SAS Visual Statistics – that enable machine learning at scale.
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SAS

OReilly: The Evolution of Analytics: Opportunities and Challenges for Machine Learning in Business

Published By: SAS     Published Date: May 17, 2016
This report provides a guide to some of the opportunities that are available for using machine learning in business, and how to overcome some of the key challenges of incorporating machine learning into an analytics strategy. We will discuss the momentum of machine learning in the current analytics landscape, the growing number of modern applications for machine learning, as well as the organizational and technological challenges businesses face when adopting machine learning. We will also look at how two specific organizations are exploiting the opportunities and overcoming the challenges of machine learning as they’ve embarked on their own analytic evolution.
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oreilly, evolution of analytics, sas, machine learning, analytics landscape, networking, it management, data management, business technology
    
SAS

THE AUTONOMOUS GRID: Machine Learning and IoT for Utilities

Published By: SAS     Published Date: Aug 04, 2016
Machine learning and the Internet of Things (IoT) are two of the hottest terms out there today for utilities. Both have the power to create an increasingly autonomous grid that can eventually handle billions of endpoints on utility networks, but the industry may not be maximizing the benefit of these disruptive innovations, nor adequately leveraging the connection between the two of them.
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best practices, networks, utility network, autonomous grid, innovation, competitive advantage, business analytics, business intelligence, business management, business technology
    
SAS

OReilly: The Evolution of Analytics: Opportunities and Challenges for Machine Learning in Business

Published By: SAS     Published Date: Jun 05, 2017
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness. Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
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SAS

Statistics and Machine Learning at Scale: New Technologies Apply Machine Learning to Big Data

Published By: SAS     Published Date: Oct 18, 2017
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications such as driverless cars. This paper, based on presentations by SAS Data Scientist Wayne Thompson, introduces key machine learning concepts and describes SAS solutions that enable data scientists and other analytical professionals to perform machine learning at scale. It tells how a SAS customer is using digital images and machine learning techniques to reduce defects in the semiconductor manufacturing process.
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SAS

Leading in the Next Analytics Age: HBR Insights The Next Analytics Age: Machine Learning

Published By: SAS     Published Date: Oct 18, 2017
What management and leadership challenges will the next wave of analytic technology bring? This SAS-sponsored Harvard Business Review Insight Center on HBR.org went beyond the buzz of what machine learning can do, to talk about how it will change companies and the way we manage them. Articles include: How to Make Your Company Machine Learning Ready, by James Hodson Machine Learning Is No Longer Just for Experts, by Josh Schwartz Teaching an Algorithm to Understand Right and Wrong, by Greg Satell The Simple Economics of Machine Intelligence, by Ajay Agrawal, Joshua Gans, and Avi Goldfarb Robots and Automation May Not Take Your Desk Job After All, by Dan Finnigan How to Tell If Machine Learning Can Solve Your Business Problem, by Anastassia Fedyk
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SAS

The Machine Learning Primer

Published By: SAS     Published Date: Oct 18, 2017
With all of the attention on machine learning, many are seeking a better understanding of this hot topic and the benefits that it could provide to their organizations. Machine learning – as well as deep learning, natural language processing and cognitive computing – are driving innovations in identifying images, personalizing marketing campaigns, genomics, and navigating the self-driving car. This e-book provides a primer on these innovative techniques as well as 10 best practices and a checklist for machine learning readiness.
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SAS

ISMG: Analytics and the AML Paradigm Shift

Published By: SAS     Published Date: Oct 18, 2017
Financial organizations are deploying artificial intelligence and machine learning in the fight against financial crimes. David Stewart, Director of Pre-Sales for the Global Security Intelligence Practice at SAS, offers tips to help separate fact from market hype when reviewing new data analytics tools. You’ll learn about: • The new industry intrigue with artificial intelligence and machine learning. • How these emerging solutions can benefit financial institutions. • The SAS approach of “crawl, walk, run” when it comes to adopting new analytics tools.
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SAS

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

Statistics and Machine Learning at Scale: New Technologies Apply Machine Learning to Big Data

Published By: SAS     Published Date: Mar 06, 2018
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the
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SAS

TDWI Best Practices Report Q3 2017: Advanced Analytics: Moving Toward AI, Machine Learning and Natur

Published By: SAS     Published Date: Mar 06, 2018
There is a lot of excitement in the market about artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Although many of these technologies have been available for decades, new advancements in compute power along with new algorithmic developments are making these technologies more attractive to early adopter companies. These organizations are embracing advanced analytics technologies for a number of reasons including improving operational efficiencies, better understanding behaviors, and gaining competitive advantage.
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SAS

The Machine Learning Primer

Published By: SAS     Published Date: Mar 06, 2018
Machines learn by studying data to detect patterns or by applying known rules to: • Categorize or catalog like people or things • Predict likely outcomes or actions based on identified patterns • Identify hitherto unknown patterns and relationships • Detect anomalous or unexpected behaviors The processes machines use to learn are known as algorithms. Different algorithms learn in different ways. As new data regarding observed responses or changes to the environment are provided to the “machine” the algorithm’s performance improves. Thereby resulting in increasing “intelligence” over time.
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SAS
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