In this 45-minute session, Jen Underwood, Founder of Impact Analytix, will review how to organize data in a machine learning-friendly format that accurately reflects the business process and outcomes. We will share basic guidelines, practical tips and additional resources to help get you started mastering the essence of predictive model data preparation.
From selecting the right problem to solve to preventing algorithm bias, machine learning is still an art and a science. To reap the benefits of automated machine learning, Jen Underwood, Founder of Impact Analytix, will share the most common mistakes - and battle-proven practices - to help you build better models.
The objective of this webinar is to help educate the federal community about the realities, and real possibilities, data science can provide. Join us to discuss how agencies can start implementing machine learning for mission success.
Colin Priest of DataRobot will explain the importance of multichannel, multi-touch attribution to accurately measure the success of your marketing efforts – and how automated machine learning offers the shortest path to success.
In this webinar, Greg Michaelson, PhD, and Head of DataRobot Labs, will review the practical first steps an organization takes towards becoming an AI-driven enterprise and remaining competitive in the coming years.
In this webinar, Justin Dickerson, General Manager of Global Finance for DataRobot, and Dan Yelle, a Customer-Facing Data Scientist for DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
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