From 48bb43100b3a34ead794784fb117eaa22c117f09 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Claus=20M=C3=B6bus?= Date: Wed, 28 Jun 2023 19:26:16 +0200 Subject: [PATCH] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index afcee29..a52795f 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,6 @@ # PCMs_SICP.jl -## Exploration of SICP, Julia, Pluto, and Data Analysis: A Personal Learning Diary +## Learn Julia, Pluto, and Data Analysis - the SICP Way - +- A self-study guide on a project-centered path - This is a personal learning-diary when exploring Julia by exploiing SICP. I used Lisp and especially Scheme regularly from time to time. I loved Scheme for its elegance and minimalism. But for production purposes in various scientic projects I had to use other languages for pragmatic reasons, like Fortran, Prolog, R, Javascript, Bugs, Stan, WebPPL and even Python. But I was always looking for a language as elegant as Scheme but with a greater usability and usefulness. Several year ago David Barber gave advice to give Julia a try. In the end I stumbled across the fascinating probabilistic programming languages Gen and Turing, both embedded in Julia. That was the starting point to deal with Julia to have a solid fundament for modeling in Gen and Turing.