US 10: Machine Learning Models for Predictive Analysis and Indicator improvement

[mvmaltitz]

Expectation:

10.1) As an analyst, I want to integrate datasets into machine learning workflows, so I can reduce inaccuracies in context-specific use cases, provide ground validation for indicators and predictive analysis trends and continuously improve outputs.

Acceptance Criteria:

10.1) Users can use uploaded datasets and data feeds in machine learning models to improve output quality and can configure how and when the data is fed into machine learning models, with the ability to track and monitor model performance over time.
10.2) Machine learning models should continuously update ground-based indicator and analysis trends.
10.3) The ML should be kept simple in phase 1 and do the following: identify the difference between what is coming on the ground (field data) and what the remote sensing data is saying.