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Our guest today is Serg Masís, author of the book "Interpretable Machine Learning with Python" and Data Scientist at Syngenta: a leading agriculture company helping to improve global food security.
In our conversation, we first talk about Serg's transition from working as a web developer to joining the world of Data Science and AI where he explains why he decided to do a master in Data Science after working in industry for over 10 years. We also discuss AI at Syngenta and explore the main challenges behind AI for agronomy. We then dig into Interpretable Machine Learning, a topic that Serg is particularly interested in. We discuss what interpretable machine learning actually means, explain different approaches and give real world examples. We finally talk about Serg's career, mistakes that he made and share advice on how to become a great Data Scientist.
Follow Serg on Linkedin: https://www.linkedin.com/in/smasis/
Subscribe to my Youtube channel: https://www.youtube.com/channel/UCWvn6k4aeceyYKjAleML9VA
Our guest today is Serg Masís, author of the book "Interpretable Machine Learning with Python" and Data Scientist at Syngenta: a leading agriculture company helping to improve global food security.
In our conversation, we first talk about Serg's transition from working as a web developer to joining the world of Data Science and AI where he explains why he decided to do a master in Data Science after working in industry for over 10 years. We also discuss AI at Syngenta and explore the main challenges behind AI for agronomy. We then dig into Interpretable Machine Learning, a topic that Serg is particularly interested in. We discuss what interpretable machine learning actually means, explain different approaches and give real world examples. We finally talk about Serg's career, mistakes that he made and share advice on how to become a great Data Scientist.
Follow Serg on Linkedin: https://www.linkedin.com/in/smasis/
Subscribe to my Youtube channel: https://www.youtube.com/channel/UCWvn6k4aeceyYKjAleML9VA
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