Name: Sangyun Kang
Type: User
Bio: Machine learning & AI enthusiast. I have a deep interest in AI, Machine learning and everything that can one day make sci-fi a reality. I love challenging.
Location: Philadelphia, PA
Blog: Branden-Kang.github.io
Sangyun Kang's Projects
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
KDD 2021: Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
A repository containing link to some my Kaggle starter Notebooks
Korean BERT pre-trained cased (KoBERT)
Physics Informed Machine Learning Tutorials (Pytorch and Jax)
A PyTorch implementation of learning shapelets from the paper Grabocka et al., „Learning Time-Series Shapelets“.
repository to accompany "A Systematic Approach to Learning Robot Programming with ROS"
Lime: Explaining the predictions of any machine learning classifier
Anomaly detection for streaming data using autoencoders
:earth_americas: machine learning tutorials (mainly in Python3)
A demo project on how to connect Materialize and Streamlit (using Redpanda & FastAPI)
Merlion: A Machine Learning Framework for Time Series Intelligence
PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"
Python tools to ease usage of MoveIt! with any robot.
A sphinx-based centralized documentation repo for MoveIt
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
This module is developed as a part of Anomaly Detection Service in AP5.