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A library that allows for inference on probabilistic models
A modern Python package and dependency manager supporting the latest PEP standards
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
An open-source tool for quick Time Series Analysis and Forecasting
This is the development home of the workflow management system Snakemake. For general information, see
Package for fitting Gaussian Process Emulators to multiple output computer simulation results.
Function-oriented Make-like declarative workflows for R
Probabilistic Numerics in Python.
Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.
Causal Inference: What If. R and Stata code for Exercises
A tool to automatically convert old string literal formatting to f-strings
Robust and effective logging for Python 2 and 3.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
Deploy a ML inference service on a budget in less than 10 lines of code.
Python library for using dplyr like syntax with pandas and SQL
tree is a library for working with nested data structures
High-performance TensorFlow library for quantitative finance.
Combining tree-boosting with Gaussian process and mixed effects models