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发布日期:2021-10-15访问次数:字号:[ ]


Introduction to Machine Learning in Agricultural and Environmental Sciences


Thursday 21/10, 15:00-18:30(北京时间)

Zoom: 960 1603 1025

Code secret : 809701


Prof. Dr. David Makowski (University Paris-Saclay and INRAE, France)


刘文丰 (


Historically, agricultural and environmental sciences have relied heavily on statistical modelling. While this approach is still very useful, machine learning has been used more and more often to analyze complex databases since the beginning of the 21st century. Machine learning methods are now often applied to predict key quantities of practical and scientific interests (agricultural yields, greenhouse gas emissions, forest biomass etc.) from algorithms that are able to take into account a large number of explanatory variables (climate, soil characteristics etc.). In this introductory course, Prof. Makowski will first present the objectives and main principles of machine learning. He will then illustrate several popular methods with examples in the field of agricultural and environmental sciences and show how to implement them with the R software.


Dr. Makowski is a research director at University Paris-Saclay and at INRAE (National Research Institute for Agriculture, Food and Environment). His main interests are in statistical modelling applied to agroecology, environmental sciences, climate change, and food safety. David manages scientific projects and supports research groups in analyzing complex datasets using statistical and machine learning methods. He is also expert for various public organizations such as the European Commission and the European Food Safety Authority. Dr. Makowski has published more than 150 scientific papers in international peer-review journals and five books on mathematical modelling, applied statistics and machine learning.

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