Search Results for "machine learning python" - Page 95
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Showing 2928 open source projects for "machine learning python"
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DeepLearnToolbox
Matlab/Octave toolbox for deep learning
DeepLearnToolbox is a MATLAB / Octave toolbox for prototyping deep learning models. It provides implementations of feedforward neural networks, convolutional neural networks (CNNs), deep belief networks (DBNs), stacked autoencoders, convolutional autoencoders, and more. The toolbox includes example scripts for each method, enabling users to quickly experiment with architectures, training, and inference workflows. Although it's been flagged as deprecated and no longer actively maintained, it... -
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libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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jLDADMM
A Java package for the LDA and DMM topic models
The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/ -
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A broad collection of command-line-interface tools for performing machine learning operations. Each tool is a thin wrapper around functionality in a well-documented C++ class library. Waffles tools are designed to be simple, script-friendly, and to
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets. To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training. To... -
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Java Library for Machine Learning
A pure Java library for machine learning
JML is a machine learning library in Java, it is a pure Java package, and thus is cross-platform. The goal of JML is to make machine learning methods very easy to use and speed up code conversion from MATLAB to Java. Please be noted that JML has been replaced by LAML. -
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Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters,...
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PSGMiner a novel software which has been developed to carry out feature extraction in order that robust analysis and classification of various sleep diseases can be performed using polysomnographic data.The software is composed of different modules: The database, feature extraction, annotation,artifact and machine learning modules. for cite İlhan Umut, PSGMiner: A modular software for polysomnographic analysis, Computers in Biology and Medicine, Volume 73, 1 June 2016, Pages 1-9, ISSN 0010-4825, http://dx.doi.org/10.1016/j.compbiomed.2016.03.023. (//www.sciencedirect.com/science/article/pii/S0010482516300750) Keywords: Computer software; Digital signal processing; Machine learning; Polysomnography APPLICATIONS Medicine: diagnosis (neurophysiology, sleep disorders tests…) Research: biomedical engineering, signal processing and machine learning Educational
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The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.
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Machine Learning framework in Python
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openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
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qwpr keylayout and layout translator
A keyboard layout that's worth learning.
Qwpr (pronounced "qwipper", named for the first four keys) is a keyboard layout that's easy to learn (only 11 keys move from their qwerty positions), easy to type (32% better by the Carpalx metric), practical (programmer's punctuation, arrow keys, and all major accented characters easily accessed without moving your hands off the three main rows), and very complete (over 1000 unicode characters and combinations available). The project also includes the tools I used to translate this... -
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TrackMania Challenge Generator
Challenge generator for racing game 'TrackMania Nations Forever'
A small tool which generates infinite number of different challenges for racing game 'TrackMania Nations Forever'. Currently only "Stadium" environment is supported. Latest release: 1.0.1.0, both English and Chinese version available. -
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Adaptive Difficulty Chinese Chess
A Chinese chess game including an adaptive computer opponent.
This project is an application of POSM algorithm on Chinese chess computer player. A computer player is implemented, which will adapt to the its opponent by adjusting its playing strength accordingly. -
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KMBOX - Kernel Methods Toolbox
A collection of kernel-based algorithms for Matlab.
KMBOX is a collection of MATLAB programs that implement kernel-based algorithms, with a focus on regression algorithms and online algorithms. It can be used for nonlinear signal processing and machine learning. -
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classify-20-NG-with-4-ML-Algo
Problem involves classifying 20000 messages into different 20 classes
This classification problem involves classifying 20000 messages into 20 different classes. The dataset can be found here: https://archive.ics.uci.edu/ml/datasets/Twenty+Newsgroups. Four Machine Learning algorithms; Naïve Bayes, Logistic Regression, Regularized Logistic Regression Support Vector Machine (SVM) were implemented and there training and test dataset accuracy were compared. Arguably, one of the most important aspect to solving this problem is having the appropriate data set format. Each of these algorithms has its peculiar data format; the specific format and how to reconstruct the entire dataset are illustrated in other sections below. ... -
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GI-ICA
Matlab implementation of GI-ICA and PEGI
This is a matlab implementation of the GI-ICA algorithm for ICA in the presence of an additive Gaussian noise. The algorithm is discussed in the paper "Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis" by James Voss, Luis Rademacher, and Mikhail Belkin. -
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Virtual Eyewear
An eyewear trying simulator
Try this software and find out the eyewear style that is the most suitable for you. -
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CILP++
In-development neural-symbolic system, CILP++
This is the project of the extension of the original C-IL2P neural-symbolic system, CILP++, for reasoning, knowledge extraction and theory revision from propositional and first-order logics. *** ATTENTION! The CILP++ project has been discontinued from SVN! It has been migrated to Github on https://github.com/manoelfranca/cilppp! -
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ankus
Data Mining and Machine Learning Algorithms based on MapReduce
[The feature of ankus] * ankus is a 'web-based big data mining project and tool'. - MapReduce-based data mining/machine learning algorithms library - Hadoop-based distributed bigdata system - offering a web-based GUI for easy use [The ankus project & License] * The ankus project consists of three as an open source. * ankus has Dual licensed under the community and commercial licenses. * community license is following GPLv3 - Some algorithms in Core Project do not under the OSS License [Demonstration Site] http://www.openankus.org:18080 [Official website & E-mail] www.openankus.org ankus@openankus.org [ankus video list] http://bit.ly/ankus_video [community] http://www.facebook.com/groups/openankus (Korean Groups) http://www.facebook.com/openankus (English Groups) http://bit.ly/ankus_forum (Google groups user forum) -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ... -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn... -
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HLearn
Homomorphic machine learning
HLearn is a Haskell-based machine learning library focused on composability, algebraic structure, and performance. It provides a functional approach to building machine learning algorithms by leveraging algebraic properties such as monoids and groups. This allows for parallel, incremental, and distributed computation in a mathematically consistent way. HLearn aims to provide implementations of common algorithms like k-means, naive Bayes, and others while maintaining the expressiveness and safety of the Haskell language. -
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GloVe
GloVe model for distributed word representation
...It collects unigram counts, constructs and shuffles cooccurrence data, and trains a simple version of the GloVe model. It also runs a word analogy evaluation script in python to verify word vector quality. -
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SteppedStateMachine
Creates and operates a stepped state machine
Implements a stepped state machine, i.e. a state machine which executes a single state transition at a time. Because of this, no data, e.g. state data, can be stored between executions. Instead, any such data must be stored in persistent storage between executions. This permits operation of the state machine as a CGI program in a web server. A WSGI or fastCGI or other such web server is not required. Received symbols may be received from sources outside the state machine, or may be...
