All Videos Tagged ML (Data Science Central) - Data Science Central 2020-06-03T01:11:27Z https://www.datasciencecentral.com/video/video/listTagged?tag=ML&rss=yes&xn_auth=no DSC Webinar Series: No-code ML for Forecasting and Anomaly Detection tag:www.datasciencecentral.com,2020-06-02:6448529:Video:955494 2020-06-02T21:36:37.902Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-no-code-ml-for-forecasting-and-anomaly"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/5526174271?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>In this latest Data Science Central webinar, we will introduce and demonstrate how you can perform common time-series Machine Learning tasks such as Forecasting and Anomaly Detection, directly within the Influx platform without the need to use external tools, languages and services<br></br> <br></br> During this webinar, you will learn:…<br></br> <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-no-code-ml-for-forecasting-and-anomaly"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/5526174271?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />In this latest Data Science Central webinar, we will introduce and demonstrate how you can perform common time-series Machine Learning tasks such as Forecasting and Anomaly Detection, directly within the Influx platform without the need to use external tools, languages and services<br /> <br /> During this webinar, you will learn:<br /> <br /> How to initiate Machine Learning tasks directly within the Influx visual interface without intimate knowledge of how these algorithms are implemented<br /> How data scientists can wrap existing, or develop new, Machine Learning algorithms for publication to the Influx time-series platform using familiar languages and frameworks <br /> <br /> Speaker: <br /> Dean Sheehan, Field CTO - InfluxData<br /> <br /> <br /> Hosted by: <br /> Stephanie Glen, Editorial Director - Data Science Central DSC Webinar Series: Embracing Responsible AI from Pilot to Production tag:www.datasciencecentral.com,2020-05-27:6448529:Video:954557 2020-05-27T22:52:42.097Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-embracing-responsible-ai-from-pilot-to"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/5403207855?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>On average, 80% of AI projects fail to make it to production. But it IS possible to successfully launch AI, at scale, that is built responsibly and works for everyone. How you scale from pilot to production is critical to ensuring AI success, while continuing to be a good corporate citizen through responsible productization. In this latest Data… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-embracing-responsible-ai-from-pilot-to"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/5403207855?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />On average, 80% of AI projects fail to make it to production. But it IS possible to successfully launch AI, at scale, that is built responsibly and works for everyone. How you scale from pilot to production is critical to ensuring AI success, while continuing to be a good corporate citizen through responsible productization. In this latest Data Science Central webinar, we’ll talk about the framework for scaling AI pilots to production with a focus on ethical responsibilities and bias mitigation at each step.<br /> <br /> We’ll look at:<br /> <br /> The five-step AI development cycle<br /> Ways to control for unwanted bias across data, models, and run time at the production layer<br /> Explainability and why it is key for moving AI pilots to production that delivers core business value<br /> <br /> Speakers: <br /> Lukas Biewald, Founder &amp; CEO - Weights &amp; Biases<br /> Alyssa Simpson Rochwerger, VP of AI &amp; Data - Appen<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: Augmented Analytics for Today’s Business User tag:www.datasciencecentral.com,2020-05-07:6448529:Video:950192 2020-05-07T20:10:34.986Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-augmented-analytics-for-today-s-business-user"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/4826601482?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Augmented Analytics is no longer the future – it’s now. <br></br> <br></br> The next generation of BI and analytics is here, and it relies heavily on AI. But with all the hype, there’s confusion about how to move forward. All too often, companies choose one-size-fits-all approaches or rely too heavily on closed, “black-box” algorithms to stand… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-augmented-analytics-for-today-s-business-user"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/4826601482?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Augmented Analytics is no longer the future – it’s now. <br /> <br /> The next generation of BI and analytics is here, and it relies heavily on AI. But with all the hype, there’s confusion about how to move forward. All too often, companies choose one-size-fits-all approaches or rely too heavily on closed, “black-box” algorithms to stand in for people. Instead, machine intelligence should work together with human intuition to unlock the best possible decision-making for people of all skill levels.<br /> <br /> In this latest Data Science Central webinar, experts from Qlik will share the latest AI-powered capabilities that enable both user-driven analytics and the democratization of data science. Attendees will get a first-hand look at:<br /> <br /> -   How AI accelerates value for all users by suggesting insights, automating tasks and supporting natural language interaction<br /> -   How organizations can deliver the power of data science and predictive models to business decision-makers in a simple, interactive way<br /> -   Demonstrations featuring Qlik’s augmented analytics capabilities, powered by our unique Associative and Cognitive Engines<br /> <br /> Speakers: <br /> Chris Mabardy, Senior Director of Product Marketing - Qlik<br /> Steven Pressland, Senior Product Manager of Augmented Intelligence - Qlik<br /> <br /> Hosted by: <br /> Sean Welch, Host &amp; Producer - Data Science Central DSC Webinar Series: A Collaborative Approach to Machine Learning tag:www.datasciencecentral.com,2020-05-06:6448529:Video:950224 2020-05-06T22:52:03.941Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-a-collaborative-approach-to-machine-learning"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/4798479864?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>It's generally accepted that you need a team with a wide variety of skills to build modern machine learning (ML) pipelines and make them operational. But what does that team look like, and how do they work together? These questions are especially important when the skills required are particularly specialized. When you’re developing… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-a-collaborative-approach-to-machine-learning"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/4798479864?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />It's generally accepted that you need a team with a wide variety of skills to build modern machine learning (ML) pipelines and make them operational. But what does that team look like, and how do they work together? These questions are especially important when the skills required are particularly specialized. When you’re developing interactive clinical and healthcare applications (backed by specialized statistical methods and made to scale on terabytes of highly complex data), you want the right people by your side. <br /> <br /> In this latest Data Science Central webinar, we'll describe 3 healthcare and life sciences projects in which business analysts, data scientists, and ML engineers collaborated. These applications and use cases are not only focused on healthcare but across a number of industries.<br /> <br /> Tune in to learn about the latest advances in big data analytics and artificial intelligence (AI) from PerkinElmer. And see real-life examples of how TIBCO data science and analytics solutions combined with the PerkinElmer AI platform can be used to create:<br /> <br /> <br /> An imaging-based phenotypic screening of cell-based disease models using high-content screening (HCS)<br /> Clinical Translational systems designed to detect and score significant biomarkers in clinical prognostication <br /> <br /> Also, find out how, in just three days, a diverse team from TIBCO responded to a critical healthcare challenge, analyzing health outcomes using socioeconomic data from countries around the world.<br /> <br /> Speakers:<br /> <br /> Alberto Pascual, Sr. Manager of AI and Analytics Innovation - PerkinElmer, Inc.<br /> Steven Hillion, Sr. Director of Data Science - TIBCO Software, Inc. <br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: How to Create Mathematical Optimization Models with Python tag:www.datasciencecentral.com,2020-04-29:6448529:Video:948616 2020-04-29T23:08:58.350Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-how-to-create-mathematical-optimization-models"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/4566482083?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>With mathematical optimization, companies can capture the key features of their business problems in an optimization model and can generate optimal solutions (which are used as the basis to make optimal decisions). Data scientists with some basic mathematical programming skills can easily learn how to build, implement, and maintain… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-how-to-create-mathematical-optimization-models"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/4566482083?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />With mathematical optimization, companies can capture the key features of their business problems in an optimization model and can generate optimal solutions (which are used as the basis to make optimal decisions). Data scientists with some basic mathematical programming skills can easily learn how to build, implement, and maintain mathematical optimization applications.<br /> <br /> The Gurobi Python API borrows ideas from modeling languages, enabling users to deploy and solve mathematical optimization models with scripts that are easy to write, read, and maintain. Such modules can even be embedded in decision support systems for production-ready applications.<br /> <br /> In this latest Data Science Central webinar, we will:<br /> <br /> Discuss the motivation for using Python in mathematical optimization applications<br /> <br /> Help you understand the importance of parameterizing a mathematical optimization model<br /> Review some of the best practices for deploying mathematical optimization models in Python<br /> <br /> Speaker: <br /> Juan Orozco Guzman, Optimization Support Engineer- Gurobi Optimization<br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central