From 8fca8161ecacfbb57929aa4f34826038d19aef88 Mon Sep 17 00:00:00 2001 From: Carlos Parada Date: Fri, 23 Dec 2022 00:40:48 +0000 Subject: [PATCH] Improve readme (#443) The improved readme taken from my previous tutorial PR. --- README.md | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index aba23c6c5..9b1b356b2 100644 --- a/README.md +++ b/README.md @@ -8,14 +8,24 @@ [![Coverage Status](https://coveralls.io/repos/github/TuringLang/DynamicPPL.jl/badge.svg?branch=master)](https://coveralls.io/github/TuringLang/DynamicPPL.jl?branch=master) [![Codecov](https://codecov.io/gh/TuringLang/DynamicPPL.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/TuringLang/DynamicPPL.jl) [![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle) -[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://colprac.sciml.ai/) +[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor%27s%20Guide-blueviolet)](https://colprac.sciml.ai/) [![Bors enabled](https://bors.tech/images/badge_small.svg)](https://app.bors.tech/repositories/24589) -A domain-specific language and backend for probabilistic programming languages, used by [Turing.jl](https://github.com/TuringLang/Turing.jl). +*A domain-specific language and backend for probabilistic programming, used by [Turing.jl](https://github.com/TuringLang/Turing.jl).* + +DynamicPPL is the part of Turing.jl that deals with defining, running, and manipulating models. DynamicPPL provides: + + - General-purpose probabilistic programming with an intuitive syntax. + - The `@model` syntax and macro for easily specifying probabilistic generative models. + - A tracing data-structure for tracking random variables in dynamic probabilistic models. + - A rich contextual dispatch system allowing for tailored behaviour during model execution. + - A user-friendly syntax for probabilistic queries. + +Information on how to use the DynamicPPL frontend to build Bayesian models can be found on the [Turing website](https://turing.ml/). Tutorials explaining how to use the backend can be found [alongside the documentation](https://turinglang.github.io/DynamicPPL.jl/stable/). More information can be found in our paper [DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models](https://arxiv.org/pdf/2002.02702.pdf). ## Do you want to contribute? -If you feel you have some relevant skills and are interested in contributing then please do get in touch and open an issue on Github. +If you feel you have some relevant skills and are interested in contributing, please get in touch! You can find us in the #turing channel on the [Julia Slack](https://julialang.org/slack/) or [Discourse](discourse.julialang.org). If you're having any problems, please open a Github issue, even if the problem seems small (like help figuring out an error message). Every issue you open helps us improve the library! ### Contributor's Guide