<p></p>
<p>Enviado de um dispositivo móvel.<br>
Sent from a mobile device. </p>
<div class="gmail_quote">---------- Mensagem encaminhada ----------<br>De: "Revolution Analytics" <<a href="mailto:info@revolutionanalytics.com">info@revolutionanalytics.com</a>><br>Data: 27/11/2012 21:49<br>
Assunto: Revolution Webinar Series: Real-time Big Data Analytics: From Deployment to Production<br>Para: <<a href="mailto:leandromarino@leandromarino.com.br">leandromarino@leandromarino.com.br</a>><br><br type="attribution">
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<img src="http://na-d.marketo.com/rs/revolutioncomputing/images/logo_revolutionanalytics_150x30.gif" align="left" border="0" height="30" width="150" alt="Revolution Analytics"><div style="color:#ff6633;font-size:16px;font-weight:bold;line-height:30px;letter-spacing:2px;text-transform:uppercase;margin-left:250px">
<div>2012 Fall Webinar Series</div>
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<div style="padding:14px"><p>Hello Everyone! There's still time to register for this Thursday's webinar "<strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/real-time-big-data-analytics/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Real-time Big Data Analytics: From Deployment to Production</a></strong>" presented by David Smith, VP of Marketing & Community at Revolution Analytics. Join us as David describes the five stages of real-time analytics deployment, the technologies supporting each stage, and how Revolution Analytics software works with the entire analytics stack to bring Big Data analytics to real-time production environments.</p>
<p><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://info.revolutionanalytics.com/real-time-big-data-analytics.html?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Reserve your seat now!</a></strong></p>
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<div style="line-height:16px;font-family:Arial,Helvetica,sans-serif;margin-bottom:0px;color:#424242;margin-left:10px;font-size:16px;font-weight:bold">Featured Webinar</div>
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<td style="padding:14px;background-color:#f1f1f1;font-size:11px;font-family:Tahoma,Helvetica;color:#45555f" colspan="2" align="center"><img src="http://www.revolutionanalytics.com/images/speakers/David-Smith-250px.jpg" alt="David Smith" width="250" height="250"></td>
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<p><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/real-time-big-data-analytics/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Real-time Big Data Analytics: From Deployment to Production</a></strong></p>
<p>As the Big Data market has evolved, the focus has shifted from data operations (storage, access and processing of data) to data science (understanding, analyzing and forecasting from data). And as new models are developed, organizations need a process for deploying analytics from research into the production environment. In this talk, we'll describe the five stages of real-time analytics deployment:</p>
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<li>Data distillation</li>
<li>Model development</li>
<li>Model validation and deployment</li>
<li>Model refresh</li>
<li>Real-time model scoring</li>
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<p>We'll review the technologies supporting each stage, and how Revolution Analytics software works with the entire analytics stack to bring Big Data analytics to real-time production environments.</p>
<p><span style="background-color:#f1f1f1;font-size:11px;font-family:Tahoma,Helvetica;color:#45555f"><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://info.revolutionanalytics.com/real-time-big-data-analytics.html?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank"><img src="http://info.revolutionanalytics.com/rs/revolutioncomputing/images/RegisterNowOrange.gif" border="0" alt="REGISTER NOW" width="177" height="39" align="left"></a></span></p>
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<td style="padding:5px;background-color:#f1f1f1;font-size:11px;font-family:Tahoma,Helvetica;color:#45555f" width="48" align="center"><img src="http://info.revolutionanalytics.com/rs/revolutioncomputing/images/User.png" border="0" alt="Presenter" width="32" height="32"></td>
<td style="padding:5px;background-color:#f1f1f1;font-size:12px;font-family:Tahoma,Helvetica;color:#45555f" width="210"><strong>David Smith</strong><br> VP Marketing & Community, Revolution Analytics</td>
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<td style="padding:5px;background-color:#f1f1f1;font-size:11px;font-family:Tahoma,Helvetica;color:#45555f" width="48" align="center"><img src="http://info.revolutionanalytics.com/rs/revolutioncomputing/images/Calendar.png" border="0" alt="Date" width="32" height="32"></td>
<td style="padding:5px;background-color:#f1f1f1;font-size:12px;font-family:Tahoma,Helvetica;color:#45555f"><strong>Thursday, November 29, 2012</strong></td>
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<td style="padding:5px;background-color:#f1f1f1;font-size:12px;font-family:Tahoma,Helvetica;color:#45555f" valign="top"><strong>10:00AM - 11:00AM Pacific Time</strong> <br> (<a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.timeanddate.com/worldclock/fixedtime.html?msg=Real-time+Big+Data+Analytics%3A+From+Deployment+to+Production&iso=20121129T10&p1=234&ah=1&mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Click here for time in your local time zone</a>)</td>
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<div style="line-height:16px;font-family:Arial,Helvetica,sans-serif;margin-bottom:0px;color:#424242;margin-left:10px;font-size:16px;font-weight:bold">Archived Webinars</div>
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<td valign="top"><strong><em>Presented Nov 15, 2012</em></strong></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/new-advances-in-high-performance-analytics-with-r/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">New Advances in High Performance Analytics with R: ‘Big Data’ Decision Trees and Analysis of Hadoop Data</a></strong>
<p>Revolution R Enterprise 6.1 includes two important advances in high performance predictive analytics with R: (1) big data decision trees, and (2) the ability to easily extract and perform predictive analytics on data stored in the Hadoop Distributed File System (HDFS).</p>
<p>Classification and regression trees are among the most frequently used algorithms for data analysis and data mining. The implementation provided in Revolution Analytics’ RevoScaleR package is parallelized, scalable, distributable, and designed with big data in mind. </p>
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<td valign="top"><strong><em>Presented Nov 8, 2012</em></strong></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/order-fulfillment-forecasting-at-john-deere/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Order Fulfillment Forecasting at John Deere: How R Facilitates Creativity and Flexibility</a></strong>
<p>Statistical analysis has been known to be invaluable to any manufactory's quality assurance for decades. Recently the value of valid statistical analysis has also been demonstrated to radically improve the ability of a company's ability to weather extreme peaks and valley in customer demand. John Deere has been able to adjust to commodity spikes and housing downturns much better than its competitors have. This is in part due to the implementation of statistical analysis and the use of R software in the order fulfillment function of John Deere.</p>
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<td valign="top"><strong><em>Presented Nov 1, 2012</em></strong></td>
<td valign="top"><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/rise-of-data-science/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank"><strong>The Rise of Data Science in the Age of Big Data Analytics: Why Data Distillation and Machine Learning Aren't Enough</strong></a>
<p>The reason why Big Data is important is because we want to use it to make sense of our world. It's tempting to think there's some "magic bullet" for analyzing big data, but simple "data distillation" often isn't enough, and unsupervised machine-learning systems can be dangerous. (Like, bringing-down-the-entire-financial-system dangerous.) Data Science is the key to unlocking insight from Big Data: by combining computer science skills with statistical analysis and a deep understanding of the data and problem we can not only make better predictions, but also fill in gaps in our knowledge, and even find answers to questions we hadn't even thought of yet.</p>
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<td valign="top"><em><strong>Presented Jun 28, 2012</strong></em></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/operational-risk-measurement-with-revoscaler/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Achieving High-Performing, Simulation-Based Operational Risk Measurement with RevoScaleR</a></strong>
<p>Under the Basel II Accord, financial institutions are required for the first time to determine capital requirements for a new class of risk – operational risk. Large and internally active banks are required to estimate operational risk exposure using the Advanced Measurement Approach (AMA), which relies on advanced empirical models. As banks continue to develop and enhance their own AMA models for operational risk measurement, they are increasingly utilizing R to perform various modeling tasks.</p>
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<td valign="top"><strong><em>Presented Jun 20, 2012</em></strong><br></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/100-percent-r-and-more/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">100% R and More: Plus What's New in Revolution R Enterprise 6.0</a></strong> <br>
<br> R users already know why the R language is the lingua franca of statisticians today: because it's the most powerful statistical language in the world. Revolution Analytics builds on the power of open source R, and adds performance, productivity and integration features to create Revolution R Enterprise. In this webinar, author and blogger David Smith will introduce the additional capabilities of Revolution R Enterprise.</td>
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<td valign="top"><strong><em>Presented Jun 5, 2012</em></strong><br></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/introduction-to-r-for-data-mining/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Introduction to R for Data Mining</a></strong> <br>
<br> We at Revolution Analytics are often asked “What is the best way to learn R?” While acknowledging that there may be as many effective learning styles as there are people we have identified three factors that greatly facilitate learning R. In this webinar, we focus on data mining as the application area and show how anyone with just a basic knowledge of elementary data mining techniques can become immediately productive in R.</td>
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<td valign="top"><strong><em>Presented May 2, 2012</em></strong><br></td>
<td valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/r-and-hadoop-equals-big-data-analytics/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">R + Hadoop = Big Data Analytics</a></strong> <br>
<br> RHadoop is an open source project spearheaded by Revolution Analytics to grant data scientists access to Hadoop’s scalability from their favorite language, R. It allows users to write general MapReduce programs, offering the full power and ecosystem of an existing, established programming language. In this webinar, Antonio will provide a brief introduction to Hadoop and R. He will describe how rmr allows R developers to program in the MapReduce framework, and provides for all developers an alternative way to implement MapReduce programs that strikes a delicate compromise between power and usability.</td>
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<td width="29%" valign="top"><strong><em>Presented Mar 28, 2012</em></strong></td>
<td width="71%" valign="top"><strong><a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/2012/actuarial-analytics-in-r/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Actuarial Analytics in R</a></strong>
<p>With data analysis showing up in domains as varied as baseball, evidence-based medicine, predicting recidivism and child support lapses, judging wine quality, credit scoring, supermarket scanner data analysis, and “genius” recommendation engines, “business analytics” is part of the zeitgeist. This is a good moment for actuaries to remember that their discipline is arguably the first – and a quarter of a millennium old – example of business analytics at work. Today, the widespread availability of sophisticated open-source statistical computing and data visualization environments provides the actuarial profession with an unprecedented opportunity to deepen its expertise as well as broaden its horizons, living up to its potential as a profession of creative and flexible data scientists. </p>
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<td colspan="2" valign="top"><em><strong>View and download all of this year's archived webinars from the <a href="http://pages.revolutionanalytics.com/track?type=click&enid=bWFpbGluZ2lkPXJldm9sdXRpb25jb21wdXRpbmdCZXRhY3VzdC0yMzMwLTYzMDMtMC0xMzc2LXByb2QtMTIwOSZtZXNzYWdlaWQ9MCZkYXRhYmFzZWlkPTEyMDkmc2VyaWFsPTEyNjUzNTM5NjQmZW1haWxpZD1sZWFuZHJvbWFyaW5vQGxlYW5kcm9tYXJpbm8uY29tLmJyJnVzZXJpZD0yMjU5MjU4LTEmZXh0cmE9JiYm&&&http://www.revolutionanalytics.com/news-events/free-webinars/?mkt_tok=3RkMMJWWfF9wsRokuK%2FJZKXonjHpfsX66ekkW6K%2BlMI%2F0ER3fOvrPUfGjI4AT8VkI%2FqLAzICFpZo2FFKH%2FaacJVU8%2FpTCE6%2FSC7ria%2Fd" target="_blank">Revolution Analytics website</a>. </strong></em>
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