Professeur titulaire/Full Professor, Département de management/ Department of Management, Faculté des sciences de l'administration / Business School Pavillon Palasis-Prince, Université Laval
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MAR 27, 2019 12:00 PM PDT
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Opportunities and Challenges for Applying Machine Learning in the Cannabis Space
Presented at:
Cannabis Sciences 2019
Speaker
Abstract
Building and production management systems are creating massive amounts of data related to growing cannabis. This presents the opportunity for growers to use machine learning (ML) tools to substantially increase their profitability and lower risk. Researchers and entrepreneurs have only recently started applying ML to agriculture, and virtually no research exists regarding cannabis. This session has three goals: 1) Introduce participants to the basic process of developing a ML model; 2) Discuss a few examples of ML being applied to non-cannabis crops that have relevance to cannabis; 3) Discuss some challenges of applying ML in the cannabis space.
Learning Objectives:
1. Learn the process of building a machine learning (ML) model.
2. Learn some likely ML application in the cannabis space and the general implementation challenges.
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MAR 27, 2019 12:00 PM PDT
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Opportunities and Challenges for Applying Machine Learning in the Cannabis Space
Presented at:
Cannabis Sciences 2019
Specialty
Molecular Biology
Laboratory Testing
Biotechnology
Research And Development
Research
Genetics
Cannabis
Functional Medicine
Microbiology
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Genetic Engineering
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