Randa Natras

Doctoral candidate at TUM; machine learning / data scientist

🔭 I’m currently working on ML-IonoCast and ML in Geodesy
🌱 I’m currently learning uncertainty quantification in AI
📫 How to reach me [email protected], [email protected]
📄 Know about my experiences https://www.linkedin.com/in/natras/ and https://www.dgfi.tum.de/en/staff/natras-randa/
⚡ Fun facts Hiking, learning languages (both programming and spoken), dancing

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Randa Natras's Projects

bayesian_neural_network_probabilistic_ionosphere_vtec

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)

ionospheric-vtec-forecasting

Example of using machine learning for forecasting Vertical Total Electron Content (VTEC) in the ionosphere

predicting-product-tier-ml-classification-

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.

predicting-the-online-views-of-products-ml-regression-

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.

quantile_gradient_boosting_probabilistic_ionosphere_vtec

This demonstrates how to load and evaluate the probabilistic Quantile Gradient Boosting (QGB) Vertical Total Electron Content (VTEC) models with 95% confidence intervals.

randa-lab

Config files for my GitHub profile.

time-series_forecasting_ma_lr_dnn_lstm

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).

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