Search Results for "statistical learning"

One more lightweight neural network in C.

Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is...

A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,...

NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolves coreference clusters using a neural network. NeuralCoref is production-ready, integrated in spaCy's NLP pipeline and extensible to new training datasets. For a brief introduction to coreference resolution and NeuralCoref, please refer to our blog post. NeuralCoref is written in Python/Cython and comes with a pre-trained statistical model for English only. NeuralCoref is accompanied by a visualization client...

iGREAT is an open-source, statistical machine translation software toolkit based on finite-state models.

An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself.

MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.

Self-Adapting Large-scale Solver Architecture: system for picking numerical algorithms (linear system solving) based on statistical modeling and machine learning.