Randa Natras's Projects
Bayesian neural network models for probabilistic VTEC forecasting with 95% confidence, from the paper "Uncertainty Quantification for Machine Learning-based Ionosphere and Space Weather Forecasting" by Natras et al. (submitted to the Space Weather, AGU)
Example of using machine learning for forecasting Vertical Total Electron Content (VTEC) in the ionosphere
This example demonstrates the prediction of the product tier of cars sold on a website from the information contained in the columns of the data 'Items_Cars_Data.csv'. The file 'Data_description.csv' describes the columns.
This example demonstrates the prediction of the detail views of cars on a website from the information contained in the other columns of the data 'Items_Cars_Data.csv'. The file 'Data_description.csv' describes the columns.
This demonstrates how to load and evaluate the probabilistic Quantile Gradient Boosting (QGB) Vertical Total Electron Content (VTEC) models with 95% confidence intervals.
Config files for my GitHub profile.
This is example demonstrates the time series forecasting using methods of Moving Average (MA), Linear Regression (LR), Deep Neural Network (DNN) and Long Short-Term Memory (LSTM).