Search Results for "machine" - Page 94
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Showing 4715 open source projects for "machine"
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Rainbow
Rainbow: Combining Improvements in Deep Reinforcement Learning
Combining improvements in deep reinforcement learning. Results and pretrained models can be found in the releases. Data-efficient Rainbow can be run using several options (note that the "unbounded" memory is implemented here in practice by manually setting the memory capacity to be the same as the maximum number of timesteps). -
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...Cheminformatics 5, 34 (2013)) for calculating molecular descriptors in various per- and polyfluroalkyl substances (PFAS). These molecular descriptors can be subsequently used in other machine learning algorithms to predict carbon-fluorine bond dissociation energies in other PFAS structures.
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RWRMTN
Predicting disease-associated miRNAs on a miRNA-target gene network
...Recently, we have proposed a computational method based on a random walk framework on a microRNA-target gene network to predict disease-associated microRNAs. This was shown superior when compared to existing state-of-the-art network- and machine learning-based methods since it well exploits mutual regulation between miRNAs and their target genes in microRNA-target gene networks. To facilitate the use of this method, we develop a Cytoscape app, named RWRMTN, to predict disease-associated microRNAs. RWRMTN can work on any microRNA-target gene network. Highly ranked microRNAs can be supported with evidence from literature. ... -
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. ... -
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RoboSat
Semantic segmentation on aerial and satellite imagery
RoboSat is an end-to-end pipeline written in Python 3 for feature extraction from aerial and satellite imagery. Features can be anything visually distinguishable in the imagery for example: buildings, parking lots, roads, or cars. -
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Open-source software for diagnostics of existing masonry structures using physics-based modeling, point clouds, and machine learning tools
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TIES
A smart search engine for medical documents
TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license. For commercial use please contact Nexi at http://nexihub.com *** NOTICE: this software and forum are no longer... -
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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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FID score for PyTorch
Compute FID scores with PyTorch
This is a port of the official implementation of Fréchet Inception Distance to PyTorch. FID is a measure of similarity between two datasets of images. It was shown to correlate well with human judgement of visual quality and is most often used to evaluate the quality of samples of Generative Adversarial Networks. FID is calculated by computing the Fréchet distance between two Gaussians fitted to feature representations of the Inception network. The weights and the model are exactly the same... -
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PivotSuite
Network Pivoting Toolkit
...Using this we can reach different subnet hosts from our pentest machine, which was only accessible from the compromised machine. -
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CakeChat
CakeChat: Emotional Generative Dialog System
...The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always bidirectional. By default, CuDNNGRU implementation is used for ~25% acceleration during inference. Thought vector is fed into decoder on each decoding step. ... -
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xLearn
High performance, easy-to-use, and scalable machine learning (ML)
xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and users is on the order of millions. ... -
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GPUImage 2
Framework for GPU-accelerated video and image processing
...The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. By relying on the GPU to run these operations, performance improvements of 100X or more over CPU-bound code can be realized. This is particularly noticeable in mobile or embedded devices. On an iPhone 4S, this framework can easily process 1080p video at over 60 FPS. On a Raspberry Pi 3, it can perform Sobel edge detection on live 720p video at over 20 FPS. -
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Active Learning
Framework and examples for active learning with machine learning model
...It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks. -
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oxSSH
oxSSH is an SSH client with multiple tools.
oxSSH is an SSH client that lets you know which tasks are running on all computers running GNU / Linux (Ubuntu, Kali Linux, Raspbian ...) via an SSH session. And it is also possible to close tasks on your running machine on GNU / Linux, reboot the SSH server, restart the SQL server (Postgres), test the SSH connection, open the oxSSH session directly on PuTTY . And if you do not have PuTTY, oxSSH will automatically install it in the oxSSH location. -
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git-flow (AVH Edition)
AVH Edition of the git extensions to provide high-level repository ops
...The files should be placed in .git/hooks In the directory hooks you can find examples of all the hooks available. You can easily publish a feature you are working on. The reason can be to allow other programmers to work on it or to access it from another machine. -
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Security Datasets
Re-play Security Events
Security‑Datasets is a community-driven repository maintained by the Open Threat Research Forge (OTRF) that curates publicly available malicious and benign datasets for threat-hunting, machine learning, event analysis, and cybersecurity research. Datasets include Windows events, logs, alerts, and simulated attack data to support detection engineering and academic research. -
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TEXT2DATA
Text Analytics Platform
Bring Text Analytics Platform that uses NLP (Natural Language Processing) and Machine Learning to your work environment. Extract essential information from your text documents and let Artificial Intelligence save your time. Get detailed and agile reports on your unstructured data. -
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Platformer 2D Godot Game
Test project with a 2D platform game developing in Godot 3.1
Test project with a 2D platform game developing in Godot 3.1, reusable mechanics for: State Machine, basics AI, Android Games. -
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MIT Deep Learning Book
MIT Deep Learning Book in PDF format by Ian Goodfellow
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville. An MIT Press book Ian Goodfellow and Yoshua Bengio and Aaron Courville. Written by three experts in the field, Deep Learning is the only comprehensive book on the subject. ... -
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jcvs
jCVS is a Java based CVS Client written by Tim Endres
...CVS is a source code control system based on RCS. The primary benefit of CVS is that it provides a server/client protocol which allows clients such as jCVS to be written. jCVS allows any Java capable machine to be a CVS client, providing for a totally distributed source code management system. -
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Microsoft Cognitive Toolkit (CNTK)
Open-source toolkit for commercial-grade distributed deep learning
CNTK describes neural networks as a series of computational steps via a digraph which are a set of nodes or vertices that are connected with the edges directed between different vertexes. Create and combine models such as: -Feed-Forward DNNs -Convolutional neural networks -Recurrent neural networks -
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handy
A simple C++11 network server framework
Simple and easy-to-use C++11 network library/ Supports tens of millions of concurrent connections on a single machine/ a simple C++11 network server framework. Graceful exit allows programmers to better define the exit behavior of their programs. You can better check for memory leaks with tools such as valgrind. 10 lines of code to write a complete server. Asynchronously manages network I/O and processes requests synchronously, which simplifies the writing of server processing logic. ... -
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NoteBook FanControl (NBFC)
Cross-platform fan control service for notebooks
...If you want to build NBFC from source, the first thing you have to do is to download the source code. You can easily clone the NBFC repository via git. Make sure the Mono runtime + development tools are installed on your machine (Debian based distros: mono-complete, Arch based distros: mono). Config files are an integral part of NBFC, because they define how NBFC interacts with your notebook's embedded controller (EC). The EC monitors your system's temperatures and controls the fan(s). It sits on the motherboard or is integrated into a Super I/O chip & is connected to the Southbridge via the Low Pin Count (LPC) bus. -
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Machine Learning Yearning
Machine Learning Yearning
Artificial intelligence, machine learning and deep learning are transforming numerous industries. Professor Andrew Ng is currently writing a book on how to build machine learning projects. The point of this book is not to teach traditional machine learning algorithms, but to teach you how to make machine learning algorithms work. Some technical courses in AI will give you a tool, and this book will teach you how to use those tools.
