This repository is publicly accessible, with all proprietary source files, data, and sensitive information removed.
The commit "Final changes" (ede9ab0
) on the main branch contains the latest presentable content for the showcase.
src/notebooks/aclabeler.py
: Defines theACLabeler
class.src/notebooks/AC_labeler.ipynb
: Notebook for labeling sample data usingACLabeler
fromsrc/notebooks/aclabeler.py
.notebooks/BART-ecg-anomaly-detection.ipynb
: Anomaly detection with autoencoder and LSTM. Also available asac_anomaly_detection.py
andac_anomaly_detection.ipynb
in thenotebooks
andscripts
sub-folders during the annotation process.data/tempseries_labeled.zip
: First 3 rows (out of 129,760) of the actual labeled time series data used inBART-ecg-anomaly-detection.ipynb
.data/labeledtimewindows/labeledtimewindows_ab_yuan.zip
: First five rows of the labels done by Steven Yuan.data/labeledtimewindows/labeledtimewindows_william.zip
: First five rows of the labels done by William Fei.data/labeledtimewindows/labeled_timewindows_conflict_yuanwilliam.zip
: First five rows of the labels done by Floyd, showing conflicts.data/labeledtimewindows_all.zip
: The combination of labels from Steven, William, and Floyd.
- Runner-up for Data Science Lifecycle Ribbon of Excellence at Berkeley's Fall 2022 Research Showcase
- Learn more about the Fall 2022 Showcase.