Model Monitoring and Anomaly Detection Part I: Introduction and The ETL Job

During my internship at The General®, I was tasked with researching and developing a system for model monitoring and anomaly detection. In the first post of this series I will discuss the importance of model monitoring: how models operate, what causes their performance to change over time, and the implications of a performance change. From there, I will introduce the overall system architecture and step through the design of the ETL load that prepares the model data for monitoring.

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James Bertrand
Growing a Data Science team (Part II)

Done intentionally, setting the strategy for what the team will accomplish can be a smooth process that generates a cycle of high value projects, team visibility and growth, and the ability to work on projects of higher value still with new modeling techniques and approaches along the way.   We will focus on how our team operates to identify areas of opportunity, and how we work with our business partners to achieve success.

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Chris Morgan
Growing a Data Science Team

Our team was created in mid-2016 and we have certainly had our share of growing pains, but we are ecstatic for the current direction we are taking and what the future holds.  We have great support from our senior leadership, which allows us to stay singularly focused on data science and to avoid the many distractions of ad hoc business analytics and “nice-to-knows” of so many data-driven questions.  How we have arrived to this point has not been by chance: we maintain a selective hiring process, have been intentional in what projects we take on, and have a clear vision.

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A Day in the Life of a Machine Learning Engineer Intern

When I stop and think about it, life is a bit crazy at the moment. I’m standing at the threshold between the end of my academic life and the beginning of my professional life. I’ve just graduated from college, moved into a house with some friends who have an impressive recording studio in their basement, and started my first ever internship with The General® as a Machine Learning Engineer (MLE) Intern.

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James Bertrand
Statistical Significance: A Survey of the Literature for the Pragmatic Data Scientist

“‘Objectivity though in practice as unattainable as infinity, is useful in the same way, at least as a fixed point of theoretical reference.  A knowledge of one’s own subjectivity is necessary in order even to contemplate the ‘objective’…Terms such as ‘neutral’, ‘detached’, let alone ‘fair-minded’, ‘disinterested’ or ‘even-handed’ do not all convey the same meaning; they are merely aestheticized forms of the same subjective aspiration.” – Christopher Hitchens, Why Orwell Matters

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Welcome, James!

This summer marks our inaugural internship program and we are fortunate to welcome James Bertrand from Belmont University. James recently completed his undergraduate studies and will focus in the Machine Learning Engineer space.


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