189: How to apply machine learning to real-world problems

189: How to apply machine learning to real-world problems

As the size and complexity of data soars exponentially, machine learning (ML) has gained prominence in applications in geoscience and related fields. ML-powered technology increasingly rivals or surpasses human performance and fuels a large range of leading-edge research. In this conversation with host Andrew Geary, mathematician Herman Jaramillo discusses his new book, Machine Learning for Science and Engineering Volume One: Fundamentals. This book teaches the underlying mathematics, terminology, and programmatic skills to implement, test, and apply ML to real-world problems. It builds the mathematical pillars required to comprehend and master modern ML concepts thoroughly and translates the newly gained mathematical understanding into better-applied data science. Herman explains why this book is a unique contribution to the growing field of machine learning, the role of intuition in using ML, and what's in this book that you rarely find in other ML books. He also goes in-depth on the critical understanding of finding the best-suited algorithm. This conversation and book explore the hottest topics facing students, scientists, and engineers. And this episode will provide a solid foundation to understand how to utilize this cutting-edge science in your work. Dr. Herman Jaramillo teaches at the University of Medellín and is a member of the Research Group on Scientific Modeling and Computing. Listen to the full archive at https://seg.org/podcast. BUY THE BOOK * Print edition (https://seg.org/shop/products/detail/588367503) * E-book (https://library.seg.org/doi/book/10.1190/1.9781560803898) CREDITS Seismic Soundoff explores the depth and usefulness of geophysics for the scientific community and the public. If you want to be the first to know about the next episode, please follow or subscribe to the podcast wherever you listen to podcasts. Two of our favorites are Apple Podcasts and Spotify. If you have episode ideas, feedback for the show, or want to sponsor a future episode, find the "Contact Seismic Soundoff" box at https://seg.org/podcast. Zach Bridges created original music for this show. Andrew Geary hosted, edited, and produced this episode at TreasureMint. The SEG podcast team is Jennifer Cobb, Kathy Gamble, and Ally McGinnis.

Episoder(301)

OTC 2026 Emerging Leaders on the Future of Offshore Energy Collaboration

OTC 2026 Emerging Leaders on the Future of Offshore Energy Collaboration

“Nothing can happen in a vacuum anymore. We need to have the developers talking to the geoscientists, talking to the environmental professionals.” Two OTC 2026 Emerging Leaders share why the future o...

23 Apr 28min

Why Seismic Acquisition Is Making a Quiet Comeback

Why Seismic Acquisition Is Making a Quiet Comeback

"What has happened in the last few years is exploration overall has taken a little bit of a backseat. So they are starting to relook at seismic acquisition to explore new areas and solve more complex ...

16 Apr 27min

From Hype to Reality: What Machine Learning Can Actually Do

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“You can't be stationary in this field. I've never seen anything like it." Machine learning is changing geophysics faster than most people expected, but knowing what actually works versus what is hyp...

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DAS and Seismic Innovation: What Geophysicists Need to Know

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"For early career geophysicists, I think it's really important to understand that DAS is going to have a unique role in reservoir management, be it onshore or offshore." Distributed acoustic sensing ...

19 Mar 27min

From Oil and Gas to Offshore Wind: Why Everyone Meets at OTC

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“And what the world really needs is this flexibility on energy and the agility to ensure access and affordability. And that's where steering the offshore energy business is really critical.” Offshore...

12 Mar 29min

Applying Near-Surface Geophysics to Agricultural Challenges

Applying Near-Surface Geophysics to Agricultural Challenges

“It’s not only about discovering resources, but about safeguarding them and safeguarding our future. When you understand the subsurface, you understand the foundation of food security, water security,...

5 Mar 26min

Inside the Workflow - Unsupervised Machine Learning for Seismic Interpretation

Inside the Workflow - Unsupervised Machine Learning for Seismic Interpretation

“The major pitfall of machine learning of any kind is to be overly confident in the results. We run the risk of garbage in gospel out.” This discussion offers a rare chance to go a little deeper into...

19 Feb 35min

Why High-Performance Computing Is No Longer Optional in Geophysics

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“I think that for geophysicists out there, people need to realize that it's an integrated career path. You can't separate the geophysics from the HPC anymore, if we ever did to begin with.” High-perf...

12 Feb 21min

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