Official repository of the Linear Arrangement Library, a library that implements state-of-the-art algorithms related to linear arrangements of graphs.
-
Updated
Jun 6, 2024 - C++
Statistics is a mathematical discipline concerned with developing and studying mathematical methods for collecting, analyzing, interpreting, and presenting large quantities of numerical data. Statistics is a highly interdisciplinary field of study with applications in fields such as physics, chemistry, life sciences, political science, and economics.
Official repository of the Linear Arrangement Library, a library that implements state-of-the-art algorithms related to linear arrangements of graphs.
🟩⬜️ Fork this repository to customize your profile! 🧑💻⭐
Data Science | AI | ML | NLP | OpenCV | Python | Statistics | SQL
📃 Duino-Coin (DUCO) network statistics & explorer website
Generate Wikidata property statistics dashboards, to be used by Wikiprojects.
Ratings for all games in Epic Games Store
One-Line Code, Open-Source, Lightweight analytics, Visualization Dashboard with an AI Data-Analyst Assistant.
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
scikit-learn: machine learning in Python
Auto-generated GitHub's profile about me with actual statistic
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
F1 statistics and data-viz
Math 2740 - Math Behind the Topics of linear algebra: least squares, singular value decomposition, principal components analysis, and graph theory: centrality, social network theory, clustering
Data and R code to accompany "A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping."
Landau Distribution Numeric Computation Memo
Phishing Domains, urls websites and threats database. We use the PyFunceble testing tool to validate the status of all known Phishing domains and provide stats to reveal how many unique domains used for Phishing are still active.
JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS