All Videos Tagged DSC Podcast Series (Data Science Central) - Data Science Central 2021-08-04T08:46:07Z https://www.datasciencecentral.com/video/video/listTagged?tag=DSC+Podcast+Series&rss=yes&xn_auth=no DSC Podcast Series: NVIDIA-Powered Data Science Solutions tag:www.datasciencecentral.com,2021-05-13:6448529:Video:1050643 2021-05-13T23:37:28.218Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-nvidia-powered-data-science-solutions"><br /> <img alt="Thumbnail" height="134" src="https://storage.ning.com/topology/rest/1.0/file/get/8927539476?profile=RESIZE_710x&amp;ss=00%3A00%3A01.000&amp;width=240&amp;height=134" width="240"></img><br /> </a> <br></br>This latest Data Science Central podcast covers how Data Science essentially spans every industry, discusses a day in the life of a data scientist working on CPUs vs. GPUs, how NVIDIA CUDA-X AI transforms data science, and – with RAPIDS and Apache ARROW in GPU Memory – implements an end-to-end GPU accelerated data science pipeline.…<br></br> <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-nvidia-powered-data-science-solutions"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/8927539476?profile=RESIZE_710x&amp;ss=00%3A00%3A01.000&amp;width=240&amp;height=134" width="240" height="134" alt="Thumbnail" /><br /> </a><br />This latest Data Science Central podcast covers how Data Science essentially spans every industry, discusses a day in the life of a data scientist working on CPUs vs. GPUs, how NVIDIA CUDA-X AI transforms data science, and – with RAPIDS and Apache ARROW in GPU Memory – implements an end-to-end GPU accelerated data science pipeline.<br /> <br /> We’ll also discuss how NVIDIA’s latest Ampere architecture-based data center and workstation GPUs, ranging from the unprecedented NVIDIA A100, the NVIDIA A40, and the category leading NVIDIA RTX A6000, RTX A5000, and RTX A4000, bring productivity and insight enhancing acceleration to data science and big data analytics professionals.<br /> <br /> Speaker: <br /> Carl Flygare, NVIDIA Professional GPU Marketing Manager - PNY<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Podcast Series: AI and Machine Learning in 20 Minutes: The AI-Powered Supply Chain tag:www.datasciencecentral.com,2021-05-13:6448529:Video:1050466 2021-05-13T23:27:29.799Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-ai-and-machine-learning-in-20-minutes-the-ai-p"><br /> <img alt="Thumbnail" height="134" src="https://storage.ning.com/topology/rest/1.0/file/get/8927534252?profile=RESIZE_710x&amp;ss=00%3A00%3A01.000&amp;width=240&amp;height=134" width="240"></img><br /> </a> <br></br>With the recent global and regional socio-economic disruptions caused by the pandemic, industries such as retail, consumer products, manufacturing, pharmaceutical, and life sciences all struggle to align production and stocking with rapidly shifting purchasing demands. At the same time, some channels have surged ahead: online retailers,… <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-ai-and-machine-learning-in-20-minutes-the-ai-p"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/8927534252?profile=RESIZE_710x&amp;ss=00%3A00%3A01.000&amp;width=240&amp;height=134" width="240" height="134" alt="Thumbnail" /><br /> </a><br />With the recent global and regional socio-economic disruptions caused by the pandemic, industries such as retail, consumer products, manufacturing, pharmaceutical, and life sciences all struggle to align production and stocking with rapidly shifting purchasing demands. At the same time, some channels have surged ahead: online retailers, delivery services, and pharmacies are thriving. In this new reality, organizations without a robust and agile predictive capability face supply chain management challenges.<br /> <br /> In this latest Data Science Central podcast, we discuss how injecting AI into existing business intelligence solutions can greatly enhance the ability of organizations to predict future demand for goods, even in uncertain and dynamic times.<br /> <br /> You’ll learn about:<br /> <br /> ·      Consumer and industry trends affecting supply chains<br /> <br /> ·      The impact of AI on supply chains within organizations implementing it<br /> <br /> ·      Real-life supply chain use cases for AI around demand, logistics, warehousing, price optimization, and more<br /> <br /> ·      The five fundamental steps organizations need to take to achieve AI-driven forecasting<br /> <br /> Speaker: <br /> Ari Kaplan, Director of AI Evangelism and Strategy - DataRobot<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Podcast Series: Looking at Feature Engineering in a Different Way tag:www.datasciencecentral.com,2021-04-08:6448529:Video:1046658 2021-04-08T21:53:52.238Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-looking-at-feature-engineering-in-a-different"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/8773751685?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Predictive modeling success hinges on selecting the features that are most likely to affect the desired outcome and sub-optimal featuring engineering is one of the culprits behind poorly performing models. In this session, we will discuss how a small number of carefully curated features can successfully serve as a proxy of predictive… <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-looking-at-feature-engineering-in-a-different"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/8773751685?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Predictive modeling success hinges on selecting the features that are most likely to affect the desired outcome and sub-optimal featuring engineering is one of the culprits behind poorly performing models. In this session, we will discuss how a small number of carefully curated features can successfully serve as a proxy of predictive characteristics across a wide range of applications. Learn how data enrichment and the use of pre-defined features can simplify feature engineering, make it more science than art, and eventually improve model quality.<br /> <br /> Speaker: <br /> Anindya Datta, CEO - Mobilewalla<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Podcast Series: The Foundation for Your AI Strategy: MLOps 101 tag:www.datasciencecentral.com,2021-03-09:6448529:Video:1042787 2021-03-09T01:53:39.581Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-the-foundation-for-your-ai-strategy-mlops-101"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/8644538478?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Organizations of all types and industries are dipping their toes into machine learning and artificial intelligence (AI). However, for most embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters.… <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-the-foundation-for-your-ai-strategy-mlops-101"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/8644538478?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Organizations of all types and industries are dipping their toes into machine learning and artificial intelligence (AI). However, for most embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters.<br /> <br /> Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability.<br /> <br /> In this latest Data Science Central podcast, The Foundation for Your AI Strategy: MLOps 101, you’ll find answers to the following questions:<br /> <br /> <br /> What is MLOps? And why is it needed for organizations in my industry to become AI-driven?<br /> What are the core elements of an MLOps infrastructure?<br /> How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects and use cases applicable to my industry?<br /> How can MLOps help data science teams, business leaders, and IT professionals build a resilient and scalable foundation for their AI initiatives?<br /> <br /> Speaker: <br /> Ari Kaplan, Director of AI Evangelism and Strategy - DataRobot<br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central DSC Podcast Series: MLOps Agents: Provide Centralized Monitoring for All Your Production Models tag:www.datasciencecentral.com,2021-03-08:6448529:Video:1042688 2021-03-08T23:58:27.916Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-mlops-agents-provide-centralized-monitoring"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/8644282693?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Machine Learning Operations (MLOps) allows organizations to deploy, manage, monitor, and govern their machine learning models from a single place, regardless of how they were created or where they are located. This empowers stakeholders to seamlessly collaborate on the common goal of scaling and managing trusted machine learning models in… <a href="https://www.datasciencecentral.com/video/dsc-podcast-series-mlops-agents-provide-centralized-monitoring"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/8644282693?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Machine Learning Operations (MLOps) allows organizations to deploy, manage, monitor, and govern their machine learning models from a single place, regardless of how they were created or where they are located. This empowers stakeholders to seamlessly collaborate on the common goal of scaling and managing trusted machine learning models in production.<br /> <br /> In this latest Data Science Central podcast, MLOps Agents: Provide Centralized Monitoring for All Your Production Models, we review how organizations can enable centralized monitoring of machine learning models using MLOps Agents.<br /> <br /> Learn how MLOps Agents:<br /> <br /> <br /> Monitor model behavior, including critical events, performance, and availability.<br /> Capture information then send it to a centralized MLOps server, making it much easier to detect and diagnose issues occurring in any production model.<br /> Track models in your preferred environment, meaning you can centrally monitor models deployed in any location on any infrastructure.<br /> <br /> Listen to this podcast to take your first step to creating a center of excellence for your production AI.<br /> <br /> Speaker: <br /> Seph Mard, Head of Model Risk, Director of Product - DataRobot<br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central