A graphical user interface to edit Pywr models

Predicting passenger survival on the Titanic using an ensemble machine learning approach, achieving a Kaggle score of 0.77990. This project leverages stacking with Random Forest, Gradient Boosting, and SVM, enhanced by feature engineering and hyperparameter tuning, to model survival patterns effectively.

Meridional ovErTurning ciRculation diagnostIC (METRIC) package for calculating observational-equivalent AMOC diagnostics in ocean general circulation models.

🤖 Manage your AI workflows effortlessly with a desktop app that features a modern GUI, CLI automation, and powerful integration options.

🎓 Analyze and predict student academic performance using socio-economic and behavioral factors with Python, enhancing educational decision-making.

💧 Forecast river discharge using machine learning with optimized ensemble models for accurate next-day predictions and flexible time series applications.

🔧 Build useful command-line tools easily with Community Toolbox, a friendly space for beginners to contribute and enhance open-source applications.

A model generator for energy system modelling and optimisation (LP/MILP).

Cloud agnostic genomics analysis, scientific computation and storage platform

CityEngine is a 3D city modeling software for urban design, visual effects, and VR/AR production. With its C++ SDK you can create plugins and standalone apps capable to execute CityEngine CGA procedural modeling rules.

A Library for publishing gltf 3d models in web

Official repo of the modular BioExcel version of HADDOCK

This repository contains all the simulation (exercises) using an open-source chemical process simulator DWSim. Shout out to Daniel Medeiros.

ApsimX is the next generation of APSIM

Bio-engineering

Open Blocks is the open source, community led evolution of Google Blocks!

The open avalanche framework

Application to run SimPEG inversions on GEOH5 files, from Geoscience ANALYST

Graphical user interface to edit, run and visualize Quetzal Models

An R package to wrap various waiting list modelling elements together for reproducibility