A time-series based machine learning model was then trained on simulated stress-strain plots for the 10,000 known orientations. At first, the simulation data were categorized as inputs (crystal ...

Meanwhile, the 1D-CNN can be used for supervised learning on time-series data. We establish a machine learning model based on the 1D-CNN by serializing Transmission Control Protocol/Internet Protocol ...

Implemented and trained XGBoost, LSTM, and WGAN-GP models for stock price forecasting, achieving robust predictive performance. Developed data preprocessing pipelines with normalization, splitting, ...

To run the pipeline for training and evaluation on time-series prediction framework, simply run $ python -m api/main_api_prediction.py or take a look at the jupyter notebook ...