Pinned Repositories
alibi-detect
Algorithms for outlier, adversarial and drift detection
AnalyticsSummit19
Material for 2019 Analytics Summit Machine Learning with R Training
applied-methods-phd
Repo for Yale Applied Empirical Methods PHD Course
AppliedPredictiveModeling
:exclamation: This is a read-only mirror of the CRAN R package repository. AppliedPredictiveModeling — Functions and Data Sets for 'Applied Predictive Modeling'. Homepage: http://appliedpredictivemodeling.com/
av-for-concept-drift-in-automl
Code for Adversarial Validation Approach to Concept Drift Problem in Automated Machine Learning Systems
awesome-causal-inference
Causal-Inference-Study-for-Analyst
가짜연구소 인과추론팀 블로그입니다!
Causal-Inference-with-Python
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
causalML-teaching
This repository consolidates my teaching material for "Causal Machine Learning".
ctv-AnomalyDetection
CRAN Task View: Anomaly Detection with R 🛒🛒🛒🛒🛒🛒🛒🛒🛒🛒🛒🛒🛒🛍️🛒🛒
SANGDONKIM's Repositories
SANGDONKIM/alibi-detect
Algorithms for outlier, adversarial and drift detection
SANGDONKIM/applied-methods-phd
Repo for Yale Applied Empirical Methods PHD Course
SANGDONKIM/AppliedPredictiveModeling
:exclamation: This is a read-only mirror of the CRAN R package repository. AppliedPredictiveModeling — Functions and Data Sets for 'Applied Predictive Modeling'. Homepage: http://appliedpredictivemodeling.com/
SANGDONKIM/awesome-causal-inference
SANGDONKIM/Causal-Inference-Study-for-Analyst
가짜연구소 인과추론팀 블로그입니다!
SANGDONKIM/Causal-Inference-with-Python
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
SANGDONKIM/causalML-teaching
This repository consolidates my teaching material for "Causal Machine Learning".
SANGDONKIM/causal-inference
SANGDONKIM/causal-inference-in-python-code
"실무로 통하는 인과추론 with 파이썬" (한빛미디어, 2024) 소스코드 저장소입니다.
SANGDONKIM/causal-ml
Must-read papers and resources related to causal inference and machine (deep) learning
SANGDONKIM/causal-text-papers
Curated research at the intersection of causal inference and natural language processing.
SANGDONKIM/credit
SANGDONKIM/distill_blog
SANGDONKIM/eurybia
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
SANGDONKIM/evidently
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
SANGDONKIM/frouros
Frouros is a Python library for drift detection in Machine Learning problems.
SANGDONKIM/ISLR-tidymodels-labs
SANGDONKIM/jobcare
SANGDONKIM/mlops-for-mle
SANGDONKIM/my_shinytutorial
SANGDONKIM/nannyml
Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance.
SANGDONKIM/Open_data_R_with_Shiny
DO IT BOOK CODE
SANGDONKIM/pack_test
SANGDONKIM/pykan
Kolmogorov Arnold Networks
SANGDONKIM/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
SANGDONKIM/rstudio-server-conda
Run Rstudio Server in a conda environment
SANGDONKIM/SANGDONKIM
SANGDONKIM/THU-Concept-Drift-Datasets-v1.0
📖These are the concept drift datasets we made, and we open-source the data and corresponding interfaces. Welcome to use them for free if there is a need.
SANGDONKIM/timeseries-playbook
슬기로운 통계생활 timeseries 공략집
SANGDONKIM/work_test