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

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: 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: