Introduction to large scale computing and data wrangling with hands-on tutorials
-
Updated
Jul 16, 2024 - HTML
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Introduction to large scale computing and data wrangling with hands-on tutorials
Particle filters, smoothers and sampling algorithms for animal movement modelling, with a focus on passive acoustic telemetry systems.
CoCalc: Collaborative Calculation in the Cloud
Agent-based modeling framework in Julia
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
Metaprogramming tools for DataFrames
High Level API Finite Element Methods based on ExtendableGrids and ExtendableFEMBase
julia matlabanalyzer to analyze the BIGG metabolic matrix
Data Apps & Dashboards for Python. No JavaScript Required.
🎈 Simple reactive notebooks for Julia
A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory.
Models for interstellar dust extinction
Documentation and tutorials for the Turing language
HDF5-compatible file format in pure Julia
A Julia Interface to the Ontology Lookup Service
RyuzakiLib is a downloader tool, there are many others
MPI wrappers for Julia
A Julia module for the data analysis of Arepo hydrodynamical simulations.
Julia bindings for various mathematical libraries (including flint2)
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012