際際滷shows by User: bluewatersql / http://www.slideshare.net/images/logo.gif 際際滷shows by User: bluewatersql / Fri, 30 Aug 2013 20:24:07 GMT 際際滷Share feed for 際際滷shows by User: bluewatersql Running with Elephants: Predictive Analytics with HDInsight /bluewatersql/running-withelephants runningwithelephants-130830202408-phpapp02
Amazon and Twitter do it, Wal-Mart & Facebook too.What about you? Big Data Predictive Analytics is pervasive and with HDInsight it's never been more approachable. In this session you become part of the demo as your clickstream data at our fictional e-commerce website drives user and product recommendations using the built-in Mahout (Taste) algorithms. In this action pack session, real-world and practical solutions for moving data into and out of HDFS (with Sqoop), using Mongo or HBase as a source/destination and of course handling Mahout processing in distributive mode will all be covered.]]>

Amazon and Twitter do it, Wal-Mart & Facebook too.What about you? Big Data Predictive Analytics is pervasive and with HDInsight it's never been more approachable. In this session you become part of the demo as your clickstream data at our fictional e-commerce website drives user and product recommendations using the built-in Mahout (Taste) algorithms. In this action pack session, real-world and practical solutions for moving data into and out of HDFS (with Sqoop), using Mongo or HBase as a source/destination and of course handling Mahout processing in distributive mode will all be covered.]]>
Fri, 30 Aug 2013 20:24:07 GMT /bluewatersql/running-withelephants bluewatersql@slideshare.net(bluewatersql) Running with Elephants: Predictive Analytics with HDInsight bluewatersql Amazon and Twitter do it, Wal-Mart & Facebook too.What about you? Big Data Predictive Analytics is pervasive and with HDInsight it's never been more approachable. In this session you become part of the demo as your clickstream data at our fictional e-commerce website drives user and product recommendations using the built-in Mahout (Taste) algorithms. In this action pack session, real-world and practical solutions for moving data into and out of HDFS (with Sqoop), using Mongo or HBase as a source/destination and of course handling Mahout processing in distributive mode will all be covered. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/runningwithelephants-130830202408-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Amazon and Twitter do it, Wal-Mart &amp; Facebook too.What about you? Big Data Predictive Analytics is pervasive and with HDInsight it&#39;s never been more approachable. In this session you become part of the demo as your clickstream data at our fictional e-commerce website drives user and product recommendations using the built-in Mahout (Taste) algorithms. In this action pack session, real-world and practical solutions for moving data into and out of HDFS (with Sqoop), using Mongo or HBase as a source/destination and of course handling Mahout processing in distributive mode will all be covered.
Running with Elephants: Predictive Analytics with HDInsight from Chris Price
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Introduction to Mahout with HDInsight /slideshow/introduction-to-mahout-with-hdinsight/24389325 mahout-130718104015-phpapp02
In this session, we will introduce a Mahout, a machine learning library that has multiple algorithms implemented on top of Hadoop and HDInsight. We will start by introducing the foundational concepts needed to understand clustering, classification and collaborative filtering before demonstrating what it takes to get started with Mahout. In addition to learning how you get Mahout set-up, you will learn what it takes to process and prepare data, how to execute an embarrassing parallel batch recommendation job and subsequently how to integrate the result back into your existing ecosystem.]]>

In this session, we will introduce a Mahout, a machine learning library that has multiple algorithms implemented on top of Hadoop and HDInsight. We will start by introducing the foundational concepts needed to understand clustering, classification and collaborative filtering before demonstrating what it takes to get started with Mahout. In addition to learning how you get Mahout set-up, you will learn what it takes to process and prepare data, how to execute an embarrassing parallel batch recommendation job and subsequently how to integrate the result back into your existing ecosystem.]]>
Thu, 18 Jul 2013 10:40:15 GMT /slideshow/introduction-to-mahout-with-hdinsight/24389325 bluewatersql@slideshare.net(bluewatersql) Introduction to Mahout with HDInsight bluewatersql In this session, we will introduce a Mahout, a machine learning library that has multiple algorithms implemented on top of Hadoop and HDInsight. We will start by introducing the foundational concepts needed to understand clustering, classification and collaborative filtering before demonstrating what it takes to get started with Mahout. In addition to learning how you get Mahout set-up, you will learn what it takes to process and prepare data, how to execute an embarrassing parallel batch recommendation job and subsequently how to integrate the result back into your existing ecosystem. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mahout-130718104015-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this session, we will introduce a Mahout, a machine learning library that has multiple algorithms implemented on top of Hadoop and HDInsight. We will start by introducing the foundational concepts needed to understand clustering, classification and collaborative filtering before demonstrating what it takes to get started with Mahout. In addition to learning how you get Mahout set-up, you will learn what it takes to process and prepare data, how to execute an embarrassing parallel batch recommendation job and subsequently how to integrate the result back into your existing ecosystem.
Introduction to Mahout with HDInsight from Chris Price
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Data Visualization with Microsoft Reporting Services /slideshow/data-visualization-24362461/24362461 datavisualization-130717213724-phpapp02
Data is beautifulor at least it can be.This session dives into the art & science behind data visualization. We will start by looking at the research done by Stephen Few and Edward Tufte to practically understand questions such as why you should prefer a bar chart over a line chart and why you typically should avoid pie charts whenever possible. Next, we will look at why Reporting Services is a rich & powerful platform for delivering your visualization before wrapping-up with techniques for implementing and delivering your eye-popping data visualizations.]]>

Data is beautifulor at least it can be.This session dives into the art & science behind data visualization. We will start by looking at the research done by Stephen Few and Edward Tufte to practically understand questions such as why you should prefer a bar chart over a line chart and why you typically should avoid pie charts whenever possible. Next, we will look at why Reporting Services is a rich & powerful platform for delivering your visualization before wrapping-up with techniques for implementing and delivering your eye-popping data visualizations.]]>
Wed, 17 Jul 2013 21:37:24 GMT /slideshow/data-visualization-24362461/24362461 bluewatersql@slideshare.net(bluewatersql) Data Visualization with Microsoft Reporting Services bluewatersql Data is beautifulor at least it can be.This session dives into the art & science behind data visualization. We will start by looking at the research done by Stephen Few and Edward Tufte to practically understand questions such as why you should prefer a bar chart over a line chart and why you typically should avoid pie charts whenever possible. Next, we will look at why Reporting Services is a rich & powerful platform for delivering your visualization before wrapping-up with techniques for implementing and delivering your eye-popping data visualizations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/datavisualization-130717213724-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Data is beautifulor at least it can be.This session dives into the art &amp; science behind data visualization. We will start by looking at the research done by Stephen Few and Edward Tufte to practically understand questions such as why you should prefer a bar chart over a line chart and why you typically should avoid pie charts whenever possible. Next, we will look at why Reporting Services is a rich &amp; powerful platform for delivering your visualization before wrapping-up with techniques for implementing and delivering your eye-popping data visualizations.
Data Visualization with Microsoft Reporting Services from Chris Price
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