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Showing 212 open source projects for "nero linux 4"
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable... -
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few... -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
GPT-2 is a Natural Language Processing model developed by OpenAI for text generation. It is the successor to the GPT (Generative Pre-trained Transformer) model trained on 40GB of text from the internet. It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a... -
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GPT-2 FR
GPT-2 French demo | Démo française de GPT-2
OpenAI GPT-2 model trained on four different datasets in French. Books in French, French film scripts, reports of parliamentary debates, Tweet by Emmanuel Macron, allowing to generate text. Tensorflow and gpt-2-simple are required in order to fine-tune GPT-2. Create an environment then install the two packages pip install tensorflow==1.14 gpt-2-simple. A script and a notebook are available in the src folder to fine-tune GPT-2 on your own datasets. The output of each workout, i.e. the folder... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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ChainerCV
ChainerCV: a Library for Deep Learning in Computer Vision
ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can... -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on... -
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Presage
the intelligent predictive text entry platform
Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic... -
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aimlGOAP
A Goal Oriented Action Planning (GOAP) implementation for AIML bots
Incorporate GOAP in your AIML bot to help it decide what to say. Requires PyGOAPng. -
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PyAIMLng
The Next Generation of Python AIML Interpreter
A Python AIML interpreter with non-compliant extensions. PyAIMLng is an interpreter for AIML (the Artificial Intelligence Markup Language), forked from Cort Stratton's PyAIML. PyAIMLng adds additional features which are not part of the AIML 1.0.1 specification in order to provide the bot master with a rich set of tools from which to build a more believable AIML bot. -
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PyGOAPng
Python Goal Oriented Action Planning (GOAP) library
A library for implementing GOAP in an AI agent. Based on pygoap v3 by Leif Theden et al. Updated code to work without having pygame installed, bug-fixed functions to make them implement the behaviors that were expected, and implemented desired behaviors so that the Pirate demo works properly for all known actions and goals. -
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ANGie
Alice Next Generation (internet entity)
An AIML based chat bot building on the original Alice AIML 1.0.1 set produced by Dr. Wallace and the ALICE AI Foundation and the PyAIML code base written by Cort Stratton, the ANGie project incorporates additional AIML sets, adds its own AIML to the set, adds new AIML tags and additional code to provide more dynamic responses and more logical case-based-reasoning. Reading through most AIML sets it seems like the authors' intention was to have a response to every input that a bot has ever... -
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Machine Learning for OpenCV
M. Beyeler (2017). Machine Learning for OpenCV
M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4. -
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Training Image Operators from Samples
Tools to train Image Operators automatically from a set of samples.
TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image. -
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cwbot
KoL chat bot
cwbot is an extensible chatbot for the Kingdom of Loathing, designed to be easy to set up and simple to extend. IMPORTANT UPDATE INFORMATION: Version 0.15.0 fixes various bugs, including an error that the bot thinks it is out of items when it really isn't. Due to a KoL server upgrade, versions older than 0.14.2 will not be able to log in to the server as of 4/12/16. Version 0.14.0 obsoletes the FaxModule. Be sure to set up the FaxModule2 to properly get faxes. Also... -
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are... -
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e-Metis - ML
Modul za napovedovanje učnih težav.
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
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Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
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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. ExSTraCS was primarily developed... -
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HYBRYD
Library written in C with Python API for IPv6 networking
This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as... -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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Unsupervised Random Forest
On-line Unsupervised Random Forest
This tool uses Random Forest and PAM to cluster observations and to calculate the dissimilarity between observations. It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm. For the sake of efficiency... -
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IMAGINE
Biological image viewer and processor
Detection, enumeration, and sizing of biological organisms by image analysis.
