How does a machine learning skeptic turn into a machine learning advocate? In Part 2, Matt recounts his data science and machine learning journey from his initial introduction and skepticism to his acceptance and forward looking thoughts on where these methods will proceed from here in oil and gas.

Matt Morris, Project Geophysical Advisor (Part 2)

This podcast series was put together by data science intern Leo Elworth to spread knowledge on these hot topics to the broader community. As the buzz around data science and machine learning continues to grow, more and more people are developing a curiosity for these topics, as well as their applications to the specific field of oil and gas. Interviews with expert data scientists and geologists serve to highlight innovative problems and share entertaining anecdotes. Podcast editing assistance was provided by Selena Garza.

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In part 2, we further discuss the role of the gig economy via the crowd in data science and machine learning, now and in the future.

Richard Copsey, Open Innovation Manager (Part 2)

Richard Copsey introduces the idea of looking "beyond the walls" for data science and machine learning solutions. New approaches like crowdsourcing can bring data science work in from a wide, external talent pool. We also discuss three specific oil and gas problems that were solved in part by the crowd.

Richard Copsey, Open Innovation Manager (Part 1)

In part 2, we get tips from Jenny for how to be a successful entrepreneur in the startup space of data science and machine learning. For instance, we cover the dos and don'ts of navigating a tech showcase as a startup.

Jenny Johnson, Emerging Technologies Incubation Manager (Part 2)

Jenny Johnson discuss how to work with emerging technologies in data science and machine learning. In particular, she walks through working with startups, and more generally the startup ecosystem, to solve business pain points requiring new data science and machine learning solutions.

Matt Morris, Project Geophysical Advisor (Part 2)

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