Robert (Munro) Monarch

pytorch_active_learning. PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book

active_learning_imagenet. Coding exercise to extend tensorflow for imagenet to active learning, for use in a job interview or similar.

uncertainty_sampling_numpy. NumPy implementations of common Active Learning strategies for Uncertainty Sampling

unicode_image_generator. Generates an image for every unicode character

disaster_response_messages. This dataset contains 25,000 messages drawn from events including an earthquake in Haiti in 2010, floods in Pakistan in 2010, super-storm Sandy in the U.S.A. in 2012, and news articles spanning a large number of years and 100s of different disasters. The data has been encoded with 38 different categories related to disaster response and has been stripped of messages with sensitive information in their entirety.

active_learning_class. Code for class on Deep Active Learning and Annotation

headlines. Practical example from Human-in-the-Loop Machine Learning book

food_safety. Practical example from Human-in-the-Loop Machine Learning book

bicycle_detection. Practical example from Human-in-the-Loop Machine Learning book

annotation_imagenet. Coding exercise to extend to create an annotation tool for ImageNet labels on Machine Learning output

chichewa. Morphological parser for the Chichewa language

deep_learning_course. Jupyter Notebook

models. Models built with TensorFlow

gender_augmentation. human-in-the-loop synthetic data generation to augment the universal dependencies corpus with gender-balanced independent possessive pronouns

char-cnn-text-classification-pytorch. Character-level Convolutional Neural Networks for text classification in PyTorch

SMS-Turks. System to help volunteers manually parse information out of text messages.