Awesome
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.