Extra: Machine Learning at John Deere with Marco Lemessi - 011
We recorded an extra and special (business related) episode, our guest is Marco Lemessi, who is a Machine Learning leader at John Deere. He will share some of the business aspects and also problems of the machine learning projects they are facing at one of the biggest agricultural companies in the world. He spent 18 years at John Deere, so you can imagine that he has a very broad perspective about business cases and data science and optimization problems at John Deere. He will talk about precision agriculture, problems of labeling on large dataset, legal aspects of artificial intelligence.
Contact Marco on LinkedIn: https://www.linkedin.com/in/marcolemessi/
Marco's email address: LemessiMarco@johndeere.com
Website of John Deere: https://www.deere.com/
---General Info---
About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer.
About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management.
About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe.
Website of the podcast: http://machinelearningcafe.org/
Host's LinkedIn: https://www.linkedin.com/in/miklostoth/
Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/
Write an email to the host: miklos@machinelearningcafe.org
Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface.
---Copyright Info---
Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
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