All Videos Tagged Data Science Central”, (Data Science Central) - Data Science Central 2021-05-13T23:00:51Z https://www.datasciencecentral.com/video/video/listTagged?tag=Data+Science+Central%E2%80%9D%2C&rss=yes&xn_auth=no DSC Webinar Series: Data Science Leadership Exchange: Best Practices for Driving Outcomes tag:www.datasciencecentral.com,2020-08-25:6448529:Video:978394 2020-08-25T22:43:07.968Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-leadership-exchange-best"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/7614174854?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Despite an increasing awareness of the role data science plays in successful business outcomes, data science leaders still struggle to organize, implement and communicate effective data science initiatives. <br></br> <br></br> Join “Data Science Leadership Exchange: Best Practices for Driving Outcomes,” and gain advice on optimizing your data management… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-leadership-exchange-best"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/7614174854?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Despite an increasing awareness of the role data science plays in successful business outcomes, data science leaders still struggle to organize, implement and communicate effective data science initiatives. <br /> <br /> Join “Data Science Leadership Exchange: Best Practices for Driving Outcomes,” and gain advice on optimizing your data management strategies. In this latest Data Science Central webinar, some of the industry’s best and brightest from Bayer, S&amp;P Global and Transamerica will be presenting their insights and experiences. <br /> <br /> Sponsored by Domino Data Lab, our distinguished group of panelists will discuss:<br /> <br /> The pros and cons of different data science organizational structures<br /> Best practices across each phase of the data science lifecycle, from model ideation through production models ops and ongoing model management<br /> Firsthand success stories — and answers to your questions<br /> <br /> Speakers: <br /> Brian Loyal, Cloud Analytics Lead - Bayer Crop Science<br /> Patrick Harrison, Director of AI Engineering - S&amp;P Global<br /> Matt Cornett, Director of Data Science - Transamerica<br /> <br /> Hosted by: <br /> Bill Vorhies, Editorial Contributor - Data Science Central DSC Webinar Series: DataOps: How Bell Canada Powers their Business with Data tag:www.datasciencecentral.com,2020-07-15:6448529:Video:962289 2020-07-15T22:44:32.762Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-dataops-how-bell-canada-powers-their-business"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/6911730865?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Agile data management has become a necessity for organizations that need to maximize the value of their data. The business is focused on outcomes but the bulk of the effort is built around data processing and delivery.  Demand for data outstrips the capacity of IT organizations and data engineering teams to deliver. New data management… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-dataops-how-bell-canada-powers-their-business"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/6911730865?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Agile data management has become a necessity for organizations that need to maximize the value of their data. The business is focused on outcomes but the bulk of the effort is built around data processing and delivery.  Demand for data outstrips the capacity of IT organizations and data engineering teams to deliver. New data management practices that adapt the practices DevOps to support data operations (DataOps) are the key to agility in data management. The enabling technologies exist today and data management practices are moving quickly toward a future of DataOps. DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics.<br /> <br /> In this latest Data Science Central webinar, you will learn:<br /> <br /> How to identify the most impactful bottlenecks sitting in the way of streamlined data processing<br /> How to evaluate multiple strategies for improving data processing outcomes and their relative impact<br /> Where to prioritize people, process, and technology changes to maximize impact<br /> How Bell revolutionized their data delivery framework by incorporating DataOps principles and technology<br /> <br /> Speakers: <br /> Johnathan Bald, Sr. Director of Sales - Hitachi Vantara<br /> Jude Vanniasinghe, Sr. Manager of Business Intelligence - Bell<br /> <br /> Presentation Moderator: <br /> Mike Williams, Global Solution Lead, Analytics and IoT - Hitachi Vantara<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: Optimization and The NFL’s Toughest Scheduling Problem tag:www.datasciencecentral.com,2020-06-23:6448529:Video:959590 2020-06-23T22:13:10.013Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-optimization-and-the-nfl-s-toughest-scheduling"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/6247863064?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Learn how the National Football League (NFL) uses mathematical optimization to solve one of the hardest scheduling problems in existence.<br></br> <br></br> At first glance, the NFL’s scheduling problem seems simple: 5 people have 12 weeks to schedule 256 games over the course of a 17-week season. The scenarios are potentially well into the… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-optimization-and-the-nfl-s-toughest-scheduling"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/6247863064?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Learn how the National Football League (NFL) uses mathematical optimization to solve one of the hardest scheduling problems in existence.<br /> <br /> At first glance, the NFL’s scheduling problem seems simple: 5 people have 12 weeks to schedule 256 games over the course of a 17-week season. The scenarios are potentially well into the quadrillions. Making the problem particularly hard is the necessary inclusion of thousands of constraints addressing stadium availability, travel considerations, competitive equity, and television viewership.<br /> <br /> In this latest Data Science Central webinar, you will learn how the NFL began using Gurobi’s mathematical optimization solver to tackle this complex scheduling problem. With mathematical optimization, NFL planners can generate and analyze more than 50,000 feasible schedules despite adding more constraints to the process every year.  Now rather than spending months manually constructing one schedule, the NFL planners can focus on evaluating and comparing thousands of completed schedules to determine which should be selected as the final schedule.   <br /> <br /> In this webinar, you will learn:<br /> <br /> How the NFL uses mathematical optimization to solve one of the most challenging scheduling problems in existence.<br /> How the NFL switched from a linear to a parallel approach to optimization.<br /> <br /> Speaker: <br /> Mike North, Vice President of NFL Broadcast Planning &amp; Scheduling - NFL<br /> <br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - 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: Learn How to Design and Deploy Optimization Applications tag:www.datasciencecentral.com,2020-05-22:6448529:Video:953426 2020-05-22T00:30:12.690Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-learn-how-to-design-and-deploy-optimization"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/5234201073?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Interested in learning how to build and deploy modern optimization applications that deliver tremendous business value?<br></br> <br></br> In this latest Data Science Central webinar, you will have the opportunity to see several live optimization application demos. These demos will showcase the power of mathematical optimization applications and… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-learn-how-to-design-and-deploy-optimization"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/5234201073?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Interested in learning how to build and deploy modern optimization applications that deliver tremendous business value?<br /> <br /> In this latest Data Science Central webinar, you will have the opportunity to see several live optimization application demos. These demos will showcase the power of mathematical optimization applications and demonstrate how you can deploy these applications on modern IT architectures like Amazon Web Services and Docker.<br /> <br /> We will cover well-known optimization problems, such as the facility location problem and workforce scheduling – we will give you an in-depth look at the user interface, the architecture, and the deployment of optimization applications. During this webinar, we will:<br /> <br /> <br /> Illustrate the business value of optimization.<br /> Demonstrate how to interact with an optimization application.<br /> Show how this application can be implemented within a modern IT architecture.<br /> Go over best practices in deploying your own optimization applications.<br /> <br /> Speaker: <br /> Richard Oberdieck, PhD, Technical Account Manager - Gurobi Optimization<br /> <br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central