NASA ARSET: Training & Testing ML Models for Irregularly-Spaced Time Series of Imagery, Part 3/3
Channel: NASA Video
Date: 20/03/2024

Large Scale Applications of Machine Learning using Remote Sensing for Building Agriculture Solutions

Part 3: Training & Testing ML Models for Irregularly-Spaced Time Series of Imagery

Trainers: Sean McCartney
Guest Instructors: John Just (Deere & Co.), Erik Sorensen (Deere & Co.)
- Perform the process to set up and train a 1-D convolutional neural network (CNN) model that learns to detect crop-type from a satellite image
- Follow steps to monitor model performance during training and how to choose appropriate hyperparameter adjustments
- Plot predictions to validate performance after training

You can access all training materials from this webinar series on the training webpage: https://go.nasa.gov/41QtlBu

This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET: https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset