All Videos Tagged Machine Learning”, ML, AI, (Data Science Central) - Data Science Central 2020-07-16T04:16:33Z https://www.datasciencecentral.com/video/video/listTagged?tag=Machine+Learning%E2%80%9D%2C+ML%2C+AI%2C&rss=yes&xn_auth=no DSC Webinar Series: Accelerating AI Adoption with Machine Learning Operations (MLOps) tag:www.datasciencecentral.com,2020-03-31:6448529:Video:941928 2020-03-31T23:12:14.852Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerating-ai-adoption-with-machine-learning"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/4287841545?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.<br></br> <br></br> In this… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerating-ai-adoption-with-machine-learning"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/4287841545?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.<br /> <br /> In this latest Data Science Central webinar, you will get an overview of MLOps and discover the issues, capabilities, and best practices required for successful and sustained deployment of machine learning in production, including:<br /> <br /> ●    The challenges of production model deployment - and how to overcome them<br /> ●    Best practices to avoid production model monitoring pitfalls<br /> ●    How to maintain high-performing models using production lifecycle management<br /> ●    Mastering production model governance to minimize risk and ensure regulatory compliance<br /> <br /> Speaker: <br /> Sivan Metzger, Managing Director, MLOps &amp; Governance - DataRobot<br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: ML/AI Models: Continuous Integration & Deployment tag:www.datasciencecentral.com,2019-12-11:6448529:Video:914196 2019-12-11T23:49:08.649Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-ml-ai-models-continuous-integration-deployme-1"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3765904026?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Some things are best learned through real-world experience. Machine learning is no different. Getting machine learning right requires evolving your analytics platform to support moving data science from research into operations. It all begins with repeatable data wrangling processes that support building and deploying models. It also… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-ml-ai-models-continuous-integration-deployme-1"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3765904026?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Some things are best learned through real-world experience. Machine learning is no different. Getting machine learning right requires evolving your analytics platform to support moving data science from research into operations. It all begins with repeatable data wrangling processes that support building and deploying models. It also requires collaboration between data scientists, engineers and business analysts. With the help of tools like SAS® Model Manager, these teams can continuously and automatically train models at scale and ensure the best models are put into production.<br /> <br /> In this latest Data Science Central webinar we will discuss:<br /> <br /> Model validation best practices<br /> Various model deployment options including open source models<br /> Model scoring and training services<br /> Model performance monitoring<br /> Orchestrating a continuous learning platform<br /> <br /> <br /> Speakers:<br /> Wayne Thompson, Chief Data Scientist - SAS<br /> Lora Edwards, Principal Product Manager - SAS<br /> <br /> Hosted by:<br /> Rafael Knuth, Contributing Editor - Data Science Central DSC Webinar Series: How Bank of America Uses Data Prep for Faster Reporting tag:www.datasciencecentral.com,2019-12-11:6448529:Video:913900 2019-12-11T00:11:20.871Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-how-bank-of-america-uses-data-prep-for-faster"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3764395366?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Knowledge workers typically a) get information b) perform logic on that information and c) finally reach a conclusion and can take action. The time to just clean and prepare data for analysis can cause significant bottlenecks and delay the ability to take any action. Automating these series of tasks, mechanizes repetitive and manual tasks.… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-how-bank-of-america-uses-data-prep-for-faster"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3764395366?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Knowledge workers typically a) get information b) perform logic on that information and c) finally reach a conclusion and can take action. The time to just clean and prepare data for analysis can cause significant bottlenecks and delay the ability to take any action. Automating these series of tasks, mechanizes repetitive and manual tasks. This frees up knowledge workers to focus on more value-added activities. A series of lessons will be shared with a case study from the banking trenches on how to leverage data wrangling to help automate these series of tasks on a use case within Risk Management and reduce a 10,000 hour regulatory process down to 10 hours.<br /> <br /> In this latest Data Science webinar you will learn:<br /> <br /> How manual and repetitive tasks are costing organizations trillions of dollars in non-productive work<br /> Understand how to drive adoption of new technologies within your organization<br /> How assembly line thinking has led to mistakes in the way we approach data pipelines<br /> <br /> Speakers:<br /> Salah Khawaja, Managing Director,<br /> Automation Global Risk - Bank of America<br /> Raj Anand, Sr. Vice President,<br /> Automation Global Risk - Bank of America<br /> Will Davis, Head of Marketing - Trifacta<br /> <br /> Hosted by:<br /> Stephanie Glen, Editorial Director - Data Science Central DSC Webinar Series: 20 Predictions for 2020 from AI to Data Management tag:www.datasciencecentral.com,2019-12-05:6448529:Video:912757 2019-12-05T01:02:06.728Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-20-predictions-for-2020-from-ai-to-data"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3755511672?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>AI, machine learning, cloud, self-service, data governance, etc…there is no shortage of buzzwords in data today. Every organization is seeking to outpace their competition by leveraging data to drive differentiation for their business. To win this race, companies are building up data science teams, investing in faster/more scalable cloud data… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-20-predictions-for-2020-from-ai-to-data"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3755511672?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />AI, machine learning, cloud, self-service, data governance, etc…there is no shortage of buzzwords in data today. Every organization is seeking to outpace their competition by leveraging data to drive differentiation for their business. To win this race, companies are building up data science teams, investing in faster/more scalable cloud data platforms and utilizing the growing variety of publicly available datasets and algorithms. How do you stay ahead of what’s next and help drive the successful adoption of new technology and processes within your organization?<br /> <br /> This latest Data Science Central webinar will be interactive and will review where we think data management, analytics and ML/AI are headed next. The session will also focus on how to use the predictions and data we share in the session to drive modernization efforts at your company.<br /> <br /> In this webinar you can expect to learn:<br /> <br /> Will cloud-native services &amp; kubernetes fundamentally change our approach to data infrastructure &amp; application integration?<br /> Will the buzz around machine learning continue or will the first ML initiatives stumble out of the gates?<br /> How will the nature of self-service change with an increased focus on data governance &amp; security?<br /> <br /> Speakers:<br /> Will Davis, Head of Marketing - Trifacta<br /> Eric Kavanagh, CEO - The Bloor Group<br /> Evren Cakir, Senior Analyst - The Bloor Group<br /> <br /> Hosted by:<br /> Stephanie Glen, Editorial Director - Data Science Central DSC Webinar Series: Demystifying AI & ML: Making Your Data Talk tag:www.datasciencecentral.com,2019-10-31:6448529:Video:904296 2019-10-31T23:17:56.244Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-demystifying-ai-ml-making-your-data-talk"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3690661941?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Learn the basics of AI and Machine Learning and understand how to improve your organization’s experience and data optimization with the power of Augmented Intelligence. Provided will be an overview of an AI strategy and you will learn about our roadmap in AI, Natural language and Machine learning. In this latest Data Science Central webinar we… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-demystifying-ai-ml-making-your-data-talk"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3690661941?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Learn the basics of AI and Machine Learning and understand how to improve your organization’s experience and data optimization with the power of Augmented Intelligence. Provided will be an overview of an AI strategy and you will learn about our roadmap in AI, Natural language and Machine learning. In this latest Data Science Central webinar we will review:<br /> <br /> Basics of AI and machine learning<br /> Importance of Augmented Intelligence vs Artificial Intelligence<br /> A unique approach to AI that allows you to make the most of your data and AI investments<br /> <br /> Speaker:<br /> Vinay Kapoor, Director, Product Management - Qlik<br /> <br /> Hosted by:<br /> Rafael Knuth, Contributing Editor - Data Science Central