Machine learning: Difference between revisions
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===Phenology Deep Learning Workshop=== | ===Phenology Deep Learning Workshop=== | ||
* [https://docs.google.com/document/d/1iHwuw_UREcvxh5Fh0C-UeefkqOClDOs0Q3LBpEDtPXw/edit?usp=sharing Agenda] | * [https://docs.google.com/document/d/1iHwuw_UREcvxh5Fh0C-UeefkqOClDOs0Q3LBpEDtPXw/edit?usp=sharing Agenda] | ||
===Presentations=== | |||
==Notes documents - Thursday== | ==Notes documents - Thursday== |
Revision as of 10:39, 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.
- Group 5 - Standards
- Group 6 - Scoring
- Group 7 - Machine learning
- Group 8 - Computational power/cyberinfrastructure
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.