Listen now | Welcome to the lecture on ML algorithms. This topic was held until the 3rd installment of this series to allow a foundation for the concept of machine learning to develop. At some point, you are going to want to operationalize your knowledge of machine learning to do some things. For the vast majority of you one of these ML algorithms will be that something. Please take a step back and consider this very real scenario. Within the general scientific community getting different results every time you run the same experiment makes publishing difficult. That does not stop authors in the ML space. Replication and the process of verifying scientific results is often difficult or impossible without similar setups and the same datasets.
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ML algorithms (ML syllabus edition 3/8)
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Listen now | Welcome to the lecture on ML algorithms. This topic was held until the 3rd installment of this series to allow a foundation for the concept of machine learning to develop. At some point, you are going to want to operationalize your knowledge of machine learning to do some things. For the vast majority of you one of these ML algorithms will be that something. Please take a step back and consider this very real scenario. Within the general scientific community getting different results every time you run the same experiment makes publishing difficult. That does not stop authors in the ML space. Replication and the process of verifying scientific results is often difficult or impossible without similar setups and the same datasets.