Machine learning is the field of study that gives computers the ability to learn from data without being explicitly programmed (Arthur Samuel, AI pioneer, 1959).
Today, applications of machine learning are everywhere and are increasingly growing. Machine learning approaches don’t require any assumption about the distribution of data. They are very robust to missing values and outliers and are performing well in non-linear systems where complex relationships exist between predictor features and the outcome.
In this introductory lecture, we aim to introduce a few machine learning methods and briefly show their applications in agriculture and livestock production.
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Funding
Intellectual climate Fund
History
School
School of Life Sciences
Publication Date
2021-12-16
Rights Statement
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