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DTSTART:20181009T160000Z
DTEND:20181009T190000Z
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SUMMARY:Analytics & Insights Forum - Oct. 9
DESCRIPTION:Scaling data science without hiring an army of data scientists -\n\nTips from the trenches\n\n\n\nPanel discussion followed by two hands-on AI sessions\n\n\n\nOrganizations are employing AI to better understand and improve their business and are seeing significant success.  Many are already planning to further expand their data science activities into other parts of the organization.  However\, you don't need to hire an army of data scientists to scale and make AI useful.  Please join us to hear a panel of enterprise organizations discuss how they employed AI solutions to kick start their AI programs using tools built to empower experts and junior data scientists.  Hands on sessions for business and technical people will immediately follow the panel to investigate using Driverless AI and open source machine learning tools.  Join the Tech Titans Analytics & Insights forum to discuss:\n\n\n	How to prepare for AI in your enterprise\n	What types of use cases deliver fast returns\n	What has worked for organizations as they employ machine learning and AI \n	What have been the failures and how you can avoid them\n	How experienced does your team need to be to succeed\n	Empowering the enterprise with Driverless AI\n\nHands on Workshops:\n\n\n\nSession 1: A Look Under the Hood of Driverless AI\n\nH2O Driverless AI is H2O.ai's flagship platform for automatic machine learning. It fully automates the data science workflow including some of the most challenging tasks in applied data science such as feature engineering\, model tuning\, model optimization\, and model deployment. Driverless AI turns Kaggle Grandmaster recipes into a full functioning platform that delivers "an expert data scientist in a box" from training to deployment.  This session will allow participants to gain hands on experience led by an H2O expert.\n\n\n\nSession 2: Productionizing H2O Models using Sparkling Water\n\nSparking Water integrates H2O with the capabilities of Apache Spark. It allows users to leverage H2O's machine learning algorithms with Apache Spark applications via Scala\, Python\, R or H2O's Flow GUI\, which makes Sparkling Water a great enterprise solution that's accessible to a wide variety of end-users. This hands-on session will allow participants to engage with multiple algorithms using Sparkling Water.\n\n\n\nPanelists: \n\nSurnjani Djoko is a principal data scientist at Wells Fargo\, with Enterprise Analytics & Data Science - Data Management and Insights organization.  She has a BS and MS in Electrical Engineering\, and Ph.D. in Computer Science & Engineering from UT Arlington with the dissertation in graph data mining.  Surnjani has worked on the advanced analytics side of financial services\, also in IT and telecom industry for many years prior to joining Wells Fargo.\n\n\n\n\n\nNutan Ranoliya\, solutions architect with AT&T\, has experience spanning Telecom\, Academia\, and the Compliance industry.  She is a pioneer in Automated AI and Machine Learning techniques at AT&T\, having been recoginzed for delivering the "Most innovative patent in 2017" at AT&T's Chief Data Office.  She earned her MS in Systems Engineering & Management at UT Dallas.  \n\n\n\n\n\n\n\nK C Tung is the principal data scientist at AT&T Xandr\, an AT&T advertising and analytic company.  KC is the lead data scientist and key architect to many industry-first\, novel\, scalable\, open-source solutions to advertisitng media's inventory planning\, audience targeting\, cross-channel execution\, testing and optimization.  KC's innovations leverage latest machine learning and AI algorithms to solve many problems in audience measurement\, attribution models\, programmatic media buys\, and social networks.  KC holds a PhD in Molecular Biophysics from UT Southwestern Medical Center.\n\n\n\n\n\n\n\n\n\nJoe Dorsey\, assistant vice president chief data office\, AT&T - During his 30+ year career in the telecom industry\, Joe has lead teams in network planning and operations\, construction & engineering\, and security.  Joe holds an MBA from Cleveland State and an Electrical Engineering degree from the University of Dayton.\n\n\n\n\n\n\n\n\n\nMayur Ranoliya\, service delivery director\, Ericsson North America Region Customer Support - With a Master's in Information Technology from UT Dallas and an Executive MBA from Harvard\, Mayur combines his entrepreneurial skills delivering strategy and hands-on technical engagement in the delivery of innovative services for Ericsson's service provider customers.  Mayur is engaged in defining best practies and methods in the use of analytics\, machine learning and artifical intelligence.
X-ALT-DESC;FMTTYPE=text/html:<p><span style="color:black\;"><span style="font-size:22px\;"><strong>Scaling data science without hiring an army of data scientists -<br />\n<em>Tips from the trenches</em></strong></span><br />\n<br />\n<em>Panel discussion followed by two hands-on AI sessions</em><br />\n<br />\nOrganizations are employing AI to better understand and improve their business and are seeing significant success.&nbsp\; Many are already planning to further expand their data science activities into other parts of the organization.&nbsp\; However\, you don&rsquo\;t need to hire an army of data scientists to scale and make AI useful.&nbsp\; Please join us to hear a panel of enterprise organizations discuss how they employed AI solutions to kick start their AI programs using tools built to empower experts and junior data scientists.&nbsp\; Hands on sessions for business and technical people will immediately follow the panel to investigate using Driverless AI and open source machine learning tools.&nbsp\; Join the Tech Titans Analytics &amp\; Insights forum to discuss:</span></p>\n\n<ul>\n	<li style="vertical-align:baseline\;"><span style="color:black\;"><span style="color:black\;">How to prepare for AI in your enterprise</span></span></li>\n	<li style="vertical-align:baseline\;"><span style="color:black\;"><span style="color:black\;">What types of use cases deliver fast returns</span></span></li>\n	<li style="vertical-align:baseline\;"><span style="color:black\;"><span style="color:black\;">What has worked for organizations as they employ machine learning and AI </span></span></li>\n	<li style="vertical-align:baseline\;"><span style="color:black\;"><span style="color:black\;">What have been the failures and how you can avoid them</span></span></li>\n	<li><span style="color:black\;"><span style="color:black\;">How experienced does your team need to be to succeed</span></span></li>\n	<li><span style="color:black\;"><span style="color:black\;">Empowering the enterprise with Driverless AI</span></span></li>\n</ul>\n<span style="color:black\;"><span style="font-size: 16px\;"><strong>Hands on Workshops:</strong></span><br />\n<br />\n<strong>Session 1: A Look Under the Hood of Driverless AI</strong><br />\nH2O Driverless AI is H2O.ai&#39\;s flagship platform for automatic machine learning. It fully automates the data science workflow including some of the most challenging tasks in applied data science such as feature engineering\, model tuning\, model optimization\, and model deployment. Driverless AI turns Kaggle Grandmaster recipes into a full functioning platform that delivers &quot\;an expert data scientist in a box&quot\; from training to deployment.&nbsp\; This session will allow participants to gain hands on experience led by an H2O expert.<br />\n<br />\n<strong>Session 2:&nbsp\;Productionizing H2O Models using Sparkling Water</strong><br />\nSparking Water integrates H2O with the capabilities of Apache Spark. It allows users to leverage H2O&#39\;s machine learning algorithms with Apache Spark applications via Scala\, Python\, R or H2O&#39\;s Flow GUI\, which makes Sparkling Water a great enterprise solution that&#39\;s accessible to a wide variety of end-users. This hands-on session will allow participants to engage with multiple algorithms using Sparkling Water.<br />\n<br />\n<em>Panelists:</em> </span>\n\n<p><span style="color:black\;"><img alt="" height="125" src="https://chambermaster.blob.core.windows.net/userfiles/UserFiles/chambers/9090/Image/SD.jpg" style="width: 125px\; height: 125px\; border-width: 2px\; border-style: solid\; margin: 5px\; float: left\;" width="125" /><strong>Surnjani Djoko</strong>&nbsp\;is a principal data scientist at Wells Fargo\, with Enterprise Analytics &amp\; Data Science - Data Management and Insights organization.&nbsp\; She has a BS and MS in Electrical Engineering\, and Ph.D. in Computer Science &amp\; Engineering from UT Arlington with the dissertation in graph data mining.&nbsp\; Surnjani has worked on the advanced analytics side of financial services\, also in IT and telecom industry for many years prior to joining Wells Fargo.<br />\n<br />\n<br />\n<img alt="" height="125" src="https://chambermaster.blob.core.windows.net/userfiles/UserFiles/chambers/9090/Image/NR.jpg" style="width: 125px\; height: 125px\; border-width: 2px\; border-style: solid\; margin: 5px\; float: left\;" width="125" /><strong>Nutan Ranoliya</strong>\, solutions architect with&nbsp\;AT&amp\;T\, has experience spanning Telecom\, Academia\, and the Compliance industry.&nbsp\; She is a pioneer in Automated AI and Machine Learning techniques at AT&amp\;T\, having been recoginzed for delivering the &quot\;Most innovative patent in 2017&quot\; at AT&amp\;T&#39\;s Chief Data Office.&nbsp\; She earned her MS in Systems Engineering &amp\; Management at UT Dallas.&nbsp\;&nbsp\;<br />\n<br />\n<br />\n<br />\n<img alt="" height="187" src="https://chambermaster.blob.core.windows.net/userfiles/UserFiles/chambers/9090/Image/KC.jpg" style="width: 125px\; height: 187px\; border-width: 2px\; border-style: solid\; margin: 5px\; float: left\;" width="125" /><strong>K C Tung</strong> is the principal data scientist at&nbsp\;AT&amp\;T Xandr\, an AT&amp\;T advertising and analytic company.&nbsp\; KC is the lead data scientist and key architect to many industry-first\, novel\, scalable\, open-source solutions to advertisitng media&#39\;s inventory planning\, audience targeting\, cross-channel execution\, testing and optimization.&nbsp\; KC&#39\;s innovations leverage latest machine learning and AI algorithms to solve many problems in audience measurement\, attribution models\, programmatic media buys\, and social networks.&nbsp\; KC holds a PhD in Molecular Biophysics from UT Southwestern Medical Center.<br />\n<br />\n<br />\n<br />\n<br />\n<img alt="" height="125" src="https://chambermaster.blob.core.windows.net/userfiles/UserFiles/chambers/9090/Image/JD.jpg" style="width: 125px\; height: 125px\; border-width: 2px\; border-style: solid\; margin: 5px\; float: left\;" width="125" /><strong>Joe Dorsey</strong>\, assistant vice president chief data office\, AT&amp\;T - During his 30+ year career in the telecom industry\, Joe has lead teams in network planning and operations\, construction &amp\; engineering\, and security.&nbsp\; Joe holds an MBA from Cleveland State and an Electrical Engineering degree from the University of Dayton.<br />\n<br />\n<br />\n<br />\n<br />\n<img alt="" height="125" src="https://chambermaster.blob.core.windows.net/userfiles/UserFiles/chambers/9090/Image/MRanoliya.jpg" style="width: 125px\; height: 125px\; border-width: 2px\; border-style: solid\; margin: 5px\; float: left\;" width="125" /><strong>Mayur Ranoliya</strong>\, service delivery director\, Ericsson North America Region Customer Support - With a Master&#39\;s&nbsp\;in Information Technology from UT Dallas and an Executive MBA from Harvard\, Mayur combines his entrepreneurial skills delivering strategy and hands-on technical engagement in the delivery of innovative services for Ericsson&#39\;s service provider customers.&nbsp\; Mayur is engaged in defining best practies and methods in the use of analytics\, machine learning and artifical intelligence.</span></p>\n<span style="color:black\;"> </span>
LOCATION:AT&T University Campus 6301 Colwell Blvd. Irving 75039
UID:e.9090.4446
SEQUENCE:3
DTSTAMP:20260420T161411Z
URL:https://business.techtitans.org/events/details/analytics-insights-forum-oct-9-4446
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