Search Results for "neural network"
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Showing 24 open source projects for "neural network"
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Monitor your whole IT InfrastructureCaters to tech staff, system Administrators, and companies of any size, from small and medium sized businesses to enterprises that need their IT network to be reliable and easy to monitor in real-time. Equipped with an easy-to-use, intuitive interface with a cutting-edge monitoring engine. PRTG optimizes connections and workloads as well as reducing operational costs by avoiding outages while saving time and controlling service level agreements (SLAs).
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Stanza
Stanford NLP Python library for many human languages
... of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data. -
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Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a tool... -
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Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations... -
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... to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. Specialized notebooks also explore creative AI applications, language modeling, generative models, and protein folding. Each tutorial is designed to be standalone and adaptable for self-study, classroom teaching, or use at summer schools and community workshops.
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Secure User Management, Made Simple | FronteggFrontegg powers modern businesses with a user management platform that’s fast to deploy and built to scale. Embed SSO, multi-tenancy, and a customer-facing admin portal using robust SDKs and APIs – no complex setup required. Designed for the Product-Led Growth era, it simplifies setup, secures your users, and frees your team to innovate. From startups to enterprises, Frontegg delivers enterprise-grade tools at zero cost to start. Kick off today.
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Hello AI World
Guide to deploying deep-learning inference networks
... your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. Follow these directions to integrate deep learning into your platform of choice and quickly develop a proof-of-concept design. -
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Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
..., establishing the groundwork for more advanced topics. Later chapters explore classic neural network structures such as CNNs, RNNs, and GANs, as well as key applications in computer vision like object detection and image segmentation. The resource also delves into optimization methods, including transfer learning, network architecture design, hyperparameter tuning, model compression, and acceleration techniques. -
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ai-edu
AI education materials for Chinese students, and teachers
Summary of open source community teaching resources for artificial intelligence education. This community is an artificial intelligence education and learning co-construction community created by the artificial intelligence education team of Microsoft Research Asia (MSRA). Under the guidance of the Ministry of Education, relying on the new generation of artificial intelligence open research and education platform, the R&D team of Microsoft Research Asia and the Academic Cooperation... -
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs... -
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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... -
OpManager the network monitoring software used by over 1 million IT adminsManageEngine OpManager is a powerful network monitoring software that provides deep visibility into the performance of your routers, switches, firewalls, load balancers, wireless LAN controllers, servers, VMs, printers, and storage devices. It is an easy-to-use and affordable network monitoring solution that allows you to drill down to the root cause of an issue and eliminate it.
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Convolution arithmetic
A technical report on convolution arithmetic in deep learning
A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory. We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures... -
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Syntactic is a simple C++ library for constructing general Neural networks. For now the library supports creation of multi layered networks for the Feedforward Backpropagation algorithm as well as Time Series Networks. More will be implemented soon.
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Neural Network class library: Its a C/C++ implementation that provides following three neural architecture - Feed-forward network, Radial Basis function network, multi-layer perceptron and Self-Organizing Maps.
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The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.
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NeuronDotNet is a neural network engine written in C#. It provides an interface for advanced AI programmers to design various types of artificial neural networks and use them.
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iSNS is an interactive neural network simulator written in Java/Java3D. The program is intended to be used in lessons of Neural Networks. The program was developed by students as the software project at Charles University in Prague.
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This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.
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Imlementation of SOM (Self organizing networks) a neural network for IBM Cell Broadband Engine Architecture.
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TIKAPP is becoming a collection of tools for simulation of neural networks. The first available part is an ANSI-C++ library with support for backpropation networks.
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Do you want a neural network OO class? With documentation? Do not go further... You found it! you have here a complete library of different neural network in an OO encapsulation. Starting from adaline, back propagation, Kohonen
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Simbrain is a java-based neural network. It is no longer being hosted here. Most information and downloads are at the homepage, www.simbrain.net. The development page is http://code.google.com/p/simbrain/
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The Pattern Recognition Analysis Project is a Java implementation of a basic multilayered backpropagation neural network, used in a color recognition and character recognition project, made for educational and experimental purposes.
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