Featured Videos - Data Science Central 2017-07-21T20:39:38Z http://www.datasciencecentral.com/video/video/rss?xn_auth=no&featured=1 Self-Service Machine Learning tag:www.datasciencecentral.com,2017-07-18:6448529:Video:593121 2017-07-18T22:50:36.477Z Tim Matteson http://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="http://www.datasciencecentral.com/video/self-service-machine-learning"><br /> <img alt="Thumbnail" height="135" src="http://api.ning.com:80/files/osVUbiELUl51WrFFbfdvPum4sP4jf5C2XHL*jVZc2nRP4op3HyLtaqDK**4tAzKbuMTDZerEbqCtR5ol-RRazitdFd5o0LmZ/1305919093.jpeg?width=240&amp;height=135" width="240"></img><br /> </a> <br></br>In today’s demanding market, Machine Learning capabilities have become a basic requirement you need to support. Self-service BI solutions are no different. Users need machine learning capabilities as an integral part of the provided solution.<br></br> <br></br> The specific challenges of integrating ML capabilities in a self-service BI platform include the supply of ML algorithms… <a href="http://www.datasciencecentral.com/video/self-service-machine-learning"><br /> <img src="http://api.ning.com:80/files/osVUbiELUl51WrFFbfdvPum4sP4jf5C2XHL*jVZc2nRP4op3HyLtaqDK**4tAzKbuMTDZerEbqCtR5ol-RRazitdFd5o0LmZ/1305919093.jpeg?width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />In today’s demanding market, Machine Learning capabilities have become a basic requirement you need to support. Self-service BI solutions are no different. Users need machine learning capabilities as an integral part of the provided solution.<br /> <br /> The specific challenges of integrating ML capabilities in a self-service BI platform include the supply of ML algorithms that do not rely on specific data and can be easily applied and fit to customer specific use cases (and data).<br /> <br /> In this Data Science Central Webinar we will demonstrate how to implement a classification model in a generic manner that can be used by many customers, without relying on specific data, and by automating the validation process ensuring minimum overfit introduced. It will outline the challenges in such a scenario and ways to mitigate them. Specifically, the case study will demonstrate implementing a Decision Tree model and visualize it using a dynamic UI component.<br /> <br /> Speakers:<br /> <br /> Nir Regev, Senior Data Scientist, Data Scientist Team Leader -- Sisense<br /> Evan Castle, Product Manager -- Sisense<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central Maximize Value of Your IoT Data tag:www.datasciencecentral.com,2017-06-29:6448529:Video:583317 2017-06-29T23:47:36.529Z Tim Matteson http://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="http://www.datasciencecentral.com/video/maximize-value-of-your-iot-data"><br /> <img alt="Thumbnail" height="135" src="http://api.ning.com:80/files/M7CqPMeJc0I0q6THQLFHDXujjh2Xro8gnyLsWLG849OBByxIp2-hABj6UKjA93Q6Vv*GbLcgO0CUsMRYyWyAzHvyQemusxPq/1300189918.jpeg?width=240&amp;height=135" width="240"></img><br /> </a> <br></br>The digital universe is expanding. Not just the data collected, but also the devices that generate that data. It is estimated there will be over 20x connected devices per person on the planet by 2020, and anything from 50-200 billion IoT devices. That’s a lot of data being generated from IoT ecosystems. The challenge will be making all that data accessible and… <a href="http://www.datasciencecentral.com/video/maximize-value-of-your-iot-data"><br /> <img src="http://api.ning.com:80/files/M7CqPMeJc0I0q6THQLFHDXujjh2Xro8gnyLsWLG849OBByxIp2-hABj6UKjA93Q6Vv*GbLcgO0CUsMRYyWyAzHvyQemusxPq/1300189918.jpeg?width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />The digital universe is expanding. Not just the data collected, but also the devices that generate that data. It is estimated there will be over 20x connected devices per person on the planet by 2020, and anything from 50-200 billion IoT devices. That’s a lot of data being generated from IoT ecosystems. The challenge will be making all that data accessible and understandable to start extracting value from it all. In this Data Science Central webinar learn how you can discover more value in your IoT data.<br /> <br /> Speaker: Adam Mayer, Senior Technical Product Marketing Manager -- Qlik<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central SPSS Statistics to Predict Customer Behavior tag:www.datasciencecentral.com,2017-06-28:6448529:Video:582816 2017-06-28T15:39:03.278Z Tim Matteson http://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="http://www.datasciencecentral.com/video/spss-statistics-to-predict-customer-behavior"><br /> <img alt="Thumbnail" height="135" src="http://api.ning.com:80/files/pJ01nIxEv7uh*beiAKYC1*YVOpLTp1*jgK3yWnTukFtO1eTxzvkuruhZv4fv6xOndZfTFFMGq7hPI6j10cBmCCIYbFoi9K0C/1299773112.jpeg?width=240&amp;height=135" width="240"></img><br /> </a> <br></br>In today’s world, every organization is collecting and storing massive amounts of data about their customers. In order to take full advantage of this data, you should be equipped with the right tools that are powerful, easier to use and able to draw accurate conclusions in understanding the motivations behind customer behaviors. These tools will allow you to… <a href="http://www.datasciencecentral.com/video/spss-statistics-to-predict-customer-behavior"><br /> <img src="http://api.ning.com:80/files/pJ01nIxEv7uh*beiAKYC1*YVOpLTp1*jgK3yWnTukFtO1eTxzvkuruhZv4fv6xOndZfTFFMGq7hPI6j10cBmCCIYbFoi9K0C/1299773112.jpeg?width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />In today’s world, every organization is collecting and storing massive amounts of data about their customers. In order to take full advantage of this data, you should be equipped with the right tools that are powerful, easier to use and able to draw accurate conclusions in understanding the motivations behind customer behaviors. These tools will allow you to derive new insights, aiding in the decision making process.<br /> <br /> In this Data Science Central webinar, you’ll see firsthand how IBM SPSS Statistics will enable you to:<br /> <br /> Quickly understand large and complex datasets using advanced statistical procedures ensuring high accuracy to drive quality decision-making<br /> Reveal deeper customer insights and provide better confidence intervals via visualizations and new analytical techniques<br /> Build a predictive enterprise making the business more agile and maximizing return on investment<br /> Speakers:<br /> <br /> Taylor Perez, Client Technical Specialist - IBM Software -- IBM Analytics<br /> Murali Prakash, Product Manager - IBM Global Markets -- IBM Analytics<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central The Myth of the Machine Learning Black Box tag:www.datasciencecentral.com,2017-06-21:6448529:Video:579744 2017-06-21T21:28:01.605Z Tim Matteson http://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="http://www.datasciencecentral.com/video/the-myth-of-the-machine-learning-black-box"><br /> <img alt="Thumbnail" height="135" src="http://api.ning.com:80/files/ZjjLUoH8OpAQ*Tor9GrqFTR2iuZWgLGHuEbF7L6vMRi8RJQxyUMPRXEZOKp2jo3VaG-caPN3OvaPQPW0sfU6S7AK7PVPonIh/1297707005.jpeg?width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Critics describe machine learning as a "black box," where data goes in and a prediction comes out, without visibility into how the prediction was derived. This lack of transparency makes it difficult to evaluate and update predictive models as conditions change or new sources of data become available. But today's machine learning systems are not black boxes,… <a href="http://www.datasciencecentral.com/video/the-myth-of-the-machine-learning-black-box"><br /> <img src="http://api.ning.com:80/files/ZjjLUoH8OpAQ*Tor9GrqFTR2iuZWgLGHuEbF7L6vMRi8RJQxyUMPRXEZOKp2jo3VaG-caPN3OvaPQPW0sfU6S7AK7PVPonIh/1297707005.jpeg?width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Critics describe machine learning as a "black box," where data goes in and a prediction comes out, without visibility into how the prediction was derived. This lack of transparency makes it difficult to evaluate and update predictive models as conditions change or new sources of data become available. But today's machine learning systems are not black boxes, allowing data scientists and business professionals alike to understand how a model makes its predictions.<br /> <br /> In this Data Science Central webinar, DataRobot will discuss how today's automated machine learning systems provide the information and visualizations that deliver deep insights that break out of the black box.<br /> <br /> Speaker: Greg Michaelson, Director of DataRobot Labs -- DataRobot<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central Level Up Your Data Science Team tag:www.datasciencecentral.com,2017-06-20:6448529:Video:579232 2017-06-20T22:00:12.096Z Tim Matteson http://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="http://www.datasciencecentral.com/video/level-up-your-data-science-team"><br /> <img alt="Thumbnail" height="135" src="http://api.ning.com:80/files/yu7QMiCGvgEC3dm6AzgUPLtNQR47JuxP4iJMG3-Oa8PgsCqPA3VmZW*N6z58ufpaBgbAJna3nsz4mrI679pBsMrRx1SUvRat/1297296368.jpeg?width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Tired of the lone wolf data scientist myth? Figured out that data science pulls people and expertise from multiple domains? Want to learn more about how to pull data science teams together to solve tough data challenges and explore the possibilities of machine learning? Join this Data Science Central webinar, “Manage Data Science in the Enterprise: Level Up Your Data… <a href="http://www.datasciencecentral.com/video/level-up-your-data-science-team"><br /> <img src="http://api.ning.com:80/files/yu7QMiCGvgEC3dm6AzgUPLtNQR47JuxP4iJMG3-Oa8PgsCqPA3VmZW*N6z58ufpaBgbAJna3nsz4mrI679pBsMrRx1SUvRat/1297296368.jpeg?width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Tired of the lone wolf data scientist myth? Figured out that data science pulls people and expertise from multiple domains? Want to learn more about how to pull data science teams together to solve tough data challenges and explore the possibilities of machine learning? Join this Data Science Central webinar, “Manage Data Science in the Enterprise: Level Up Your Data Science Team" and learn data science best practices, tools, and techniques to increase collaboration and productivity.<br /> <br /> Speakers:<br /> <br /> Carlo Appugliese, Big Data and Data Science Evangelist -- IBM Analytics, Watson and Cloud Platform<br /> Alex Jones, IBM Offering Manager, Data Science Experience Local -- IBM Analytics, Watson Data Platform<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central