Causal analysis to predict factors affecting employee resignation using the Causal Inference method on company datasets.
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Updated
Jun 24, 2024 - Jupyter Notebook
Causal analysis to predict factors affecting employee resignation using the Causal Inference method on company datasets.
YLearn, a pun of "learn why", is a python package for causal inference
A resource list for causality in statistics, data science and physics
Python package for causal discovery based on LiNGAM.
Eliot: the logging system that tells you *why* it happened
가짜연구소 <인과추론과 실무> 프로젝트
A super light-weight web app to create causal loop diagrams (CLD) online. This is useful in Systems Thinking and System Dynamics.
Researching causal relationships in time series data using Temporal Convolutional Networks (TCNs) combined with attention mechanisms. This approach aims to identify complex temporal interactions. Additionally, we're incorporating uncertainty quantification to enhance the reliability of our causal predictions.
Artificial Intelligence Notes (causal inference)
Hyper-geometric computational causality library for Rust
CausalVerse: An R toolkit expediting causal research & analysis. Streamlines complex methodologies, empowering users to unveil causal relationships with precision. Your go-to for insightful causality exploration.
Python library for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Causing: CAUsal INterpretation using Graphs
ESA-2SCM for Causal Discovery: Causal Modeling with Elastic Segmentation-based Synthetic Instrumental Variable
Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.
Here you will find my Data science and Machine learning Projects
Python package for Granger causality test with nonlinear forecasting methods.
Tutorials for the synthetic control method for causal inference using PyMC
A project for exploring differentially active signaling paths related to proteomics datasets
A Python package for causal inference using Synthetic Controls
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