Project Overview

Learning Objectives: What would the user learn completing the module

• Being comfortable with accessing and creating analysis pipelines for image-based data.
• Learning how to clean/prepare/balance datasets for training ML models
• Getting familiar with different Python tools for data analysis and visualization
• Getting familiar with PyTorch/Torch Vision
• Applying classification models to medical image and/or satellite data.
• Applying segmentation models to medical image and/or satellite data.
• Loading pre-trained image models and performing transfer learning.
• Understanding what interactive machine learning is, and why/how it is important in social good applications (i.e. counting/classifying biodiversity data, providing labels for unlabeled data, and asking a park ranger to assist when it is uncertain about a classification)
• Familiarity with some of the state-of-the-art literature for active learning/computer vision for social good.