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A library for generative social simulation
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality!
hadley / multiverse
Forked from MUCollective/multiverseR package for creating explorable multiverse analysis
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
Draw flows (migration, goods, money, information) on ggplots.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Uplift modeling and causal inference with machine learning algorithms
Generate Diverse Counterfactual Explanations for any machine learning model.
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
The idea is to pass matrices/vectors from R to C++, write pure C++/Armadillo code for the computation, and then export the result back to R with the proper data structures.
A template for scikit-learn extensions
A massively parallel, high-level programming language
A Python library that helps data scientists to infer causation rather than observing correlation.
DoubleML - Double Machine Learning in Python
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Time2Feat: Learning Interpretable Representations for Multivariate Time Series Clustering
Package to calculate cool routes through cities
