ELSI-DL-Bootcamp

Intro to Machine Learning and Deep Learning for Earth-Life Sciences

Slides

ML Research Project Management

Intro to Deep Learning

Intro to Convolutional Neural Networks

Notebooks

Exploratory Data Analysis

Data Visualization

Train a Convolutional Neural Network

Data: Kaggle - DeepSat (SAT-6) Airborne Dataset

405,000 image patches each of size 28x28 and covering 6 landcover classes

Content

• Each sample image is 28x28 pixels and consists of 4 bands - red, green, blue and near infrared.
• The training and test labels are one-hot encoded 1x6 vectors
• The six classes represent the six broad land covers which include barren land, trees, grassland, roads, buildings and water bodies.
• Training and test datasets belong to disjoint set of image tiles.
• Each image patch is size normalized to 28x28 pixels.
• Once generated, both the training and testing datasets were randomized using a pseudo-random number generator.