Bayesian Modeling and Probabilistic Programming in Python
- python
- statistical-analysis
- bayesian-inference
- mcmc
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Bayesian Modeling and Probabilistic Programming in Python
Deep universal probabilistic programming with Python and PyTorch
Scalable and user friendly neural :brain: forecasting algorithms.
Fast, flexible and easy to use probabilistic modelling in Python.
Python Toolkit for Causal and Probabilistic Reasoning
Beautiful, open source, WebGPU-based charting library
Large list of handpicked color names 🌈
Daily radar for new AI terms: names of new models, products and repos, caught on X, Hugging Face, GitHub and sitemaps before keyword tools list them.
The Python ensemble sampling toolkit for affine-invariant MCMC
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
A simple Python data-structure visualization tool for lists of lists, lists, dictionaries; primarily for use in Jupyter notebooks / presentations
Algorithm is a library of tools that is used to create intelligent applications.
A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
A Toolbox for Non-Tabular Data Manipulation
Common Lisp Statistics -- based on LispStat (Tierney) but updated for Common Lisp and incorporating lessons from R (http://www.r-project.org/). See the google group for lisp stat / common lisp statistics for a mailing list.
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
Social Determinants of Health Visualization
Minimalistic statistics library for Clojure
Probabilistic computation in Idris
A simple author handler for scientific writing
Statistics module for MicroPython