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Minitab
Predictive Analytics Webinar Series 2024

Leverage the power of predictive analytics with Minitab.

Learn about the benefits of Predictive Analytics with our yearly webinar series presented by Minitab’s Senior Advisory Data Scientist, Mikhail Golovnya. Explore the potential of Artificial Intelligence (AI) and Machine Learning as we delve into modern banking and humanitarian use cases. 

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Minitab Statistical Software: Exploring Reliable, Rule-Based AI and Automated Machine Learning

Webinar 1

Exploring Reliable, Rule-Based AI and Automated Machine Learning

Join us as we introduce the fundamental concepts and diverse types of Artificial Intelligence (AI), with a focus on Machine Learning. We will delve into the world of automated machine learning, where we unveil how AI revolutionizes model building, empowering you to create more accurate and efficient models. Discover the secrets to unlocking the best solutions for your predictive analytics challenges and identifying the most impactful predictor subsets. You can review the presentation slides here. Click here to view the presentation slides.
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Model deployment capabilities with Minitab

Webinar 2

Mastering Model Optimization with Artificial Intelligence (AI)

This webinar will focus on model deployment, which is crucial to project success – and often a point of failure. We'll show how modern predictive models can be converted into traditional formula-based formats while highlighting the challenges and pitfalls.  We also introduce Minitab’s predictive model deployment solution (Model Ops) - an advanced web-based solution for seamless model deployment. Learn how to deploy a real-time model predicting wind turbine failures. Don't miss this opportunity to learn how Model Ops can streamline your deployment needs. Click here to view the presentation slides.
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model monitoring with minitab

Webinar 3

Model Deployment: Monitoring, Diagnostics, and Predictive Concepts

On the third and final day of Predictive Analytics Week ‘24, we’ll investigate model deployment issues and introduce powerful model monitoring tools available in Minitab’s Model Deployment solution. We explain the key concepts of data drift and model drift which are often responsible for model failure over time. See how Model Ops handles and monitors individual models in real-time and what diagnostics are available. We wrap things up by exploring the future of predictive analytics while highlighting the important role it plays. Click here to view the presentation slides.
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About the Presenter 

Mikhail Golovnya, Senior Advisory Data Scientist at Minitab, has been prototyping new machine learning algorithms and modeling automation for the past twenty years. He has been a major contributor to Salford Systems/Minitab’s on-going search for technological improvements among the most important algorithms in Machine Learning: CART® Decision Trees, MARS® Non-linear Regression, TreeNet® gradient boosting, and Random Forests®. Mikhail has presented at multiple conferences and seminars. He has also taught about the mathematical foundations and applications of major predictive learning algorithms, both classical and modern. He has two master’s degrees, one in rocket science from Kharkov State Polytechnic University (Ukraine) and another in statistical computing from the University of Central Florida (Orlando). Mikhail is leading the next generation of Minitab’s machine learning product development.

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