Difference between revisions of "Machine learning"

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(Presentations)
(Presentations)
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* [[Media:White.IDigBio_DL_workshop.pdf|Alex White]]
 
* [[Media:White.IDigBio_DL_workshop.pdf|Alex White]]
 
* [[Media:Pearson.CAP_DeepLearningWorkshop2.pdf|Katie Pearson]]
 
* [[Media:Pearson.CAP_DeepLearningWorkshop2.pdf|Katie Pearson]]
 +
* [[Media:Sweeney.Pheno_in_the_Machine_Sweeney_2019.pdf|Patrick Sweeney]]
  
 
==Notes documents - Thursday==
 
==Notes documents - Thursday==

Revision as of 10:55, 18 January 2019

Phenology Deep Learning Workshop

Presentations

Notes documents - Thursday

Round One Assignment: Write the thesis paragraph for a paper outlining the major components of the perfect system for acquiring and managing phenological data from plant specimens. Restrict your paragraph to 6 sentences, the topic sentence and 5 supporting sentences addressing the 5 major components your paper will elucidate. Arrange your 5 sentences in priority order.

Round Two Assignment: From round one, several major topics cut across most of your responses, including standards, scoring, machine learning, Computational power/cyberinfrastructure. Self-select into four groups and outline where we are and where we want to go for these components.

Notes documents - Friday

Round Three Assignment: From our discussions on Day 1, record what you recognize as priority issues that need to be addressed first. Think of this in terms of a project. If funds were available to begin a project, what are the critical outcomes the project should strive to achieve?

Round Four Assignment: Continuing with our project development scenario, self-select the components you are most interested in and in small groups, begin to add implementation steps to our project, thinking as concretely as possible and making a strong and convincing case for the components you envision.