Search Results for "learning"

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code

See TTS demo at: http://rslp.racai.ro/index.php?page=tts This is an entirely written in JAVA project which includes a set of tools and methods designed to enable Multilingual Text-to-Speech (TTS) synthesis. We currently support English and Romanian but we will soon train more models and make them available for download. If you want to read more about our other NLP and TTS tools check out http://nlptools.racai.ro.

R-Portfolio - breakeven optimally diversified investment portfolio. Оптимально диверсифицированный инвестиционный портфель.

Machine learning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).

BabyTALK is to add another brick in the wall of natural languages learning. The baby needs to structure a corpus of texts when his tutor points and talks about a particular part of the corpus. The baby is also to describe any selected part of the corpus.

mlearn is a gradient based learning toolbox for matlab. While it is fairly simple to build a neural network, it is designed for ease of implementing new kind of gradient based architecture.

Java/XML toolkit for research using Bayesian networks and other graphical models of probability (exact and approximate inference, structure learning, etc.)

Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.