Rohan Nuttall's repositories
ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
attention-cnn
Source code for "On the Relationship between Self-Attention and Convolutional Layers"
BayesianOptimization
A Python implementation of global optimization with gaussian processes.
BladderDataset
This machine learning system can diagnose 2 acute inflammations of bladder. The medical dataset contains features and diagnoses of 2 diseases of the urinary system: Inflammation of urinary bladder and nephritis of renal pelvis origin. This medical dataset truly needs privacy! Because we cannot divulge the sexually-transmitted diseases of patients. So, what we learned about PySyft and OpenMined is applied in this project. Federated learning will protect the privacy of datasets in each hospital and at the same time, a more robust machine learning model will benefit all hospitals. Why? Because the machine learning model generated in this project is 100% accurate; whereas human doctors can commit mistakes when diagnosing these 2 diseases.
causalML-1
A course on causal machine learning.
electricitymap-contrib
A real-time visualisation of the CO2 emissions of electricity consumption
Environmental_Intelligence
Data for Environmental Intelligence: A mega list of Earth System Datasets covering earth observations, climate, water, forests, biodiversity, ecology, protected areas, natural hazards, marine and the tracking of UN's Sustainable Development Goals
Federated-Learning-PyTorch
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
MAP-Elites
Python implementation of the genetic algorithm MAP-Elites with applications in constrained optimization
MBRL-HVAC-Energy-Optimization
A reference solution for using model-based reinforcement learning to train energy utilization-minimizing HVAC control agents. Developed by TELUS with support from Vector Institute.
ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
nowcasting_dataset
Prepare batches of data for training machine learning solar electricity nowcasting data
predict_pv_yield
Use machine learning to map from satellite imagery of clouds to solar PV yield
probability
Probabilistic reasoning and statistical analysis in TensorFlow
pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
rl-testbed-for-energyplus
Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus
social-cost-convenience
Code for social cost of commuting convenience
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
ubcv_campus_water_map
A map containing data related to UBC water management