Search Results for "tiny-core-plus" - Page 8
Sort By:
Showing 254 open source projects for "tiny-core-plus"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance.... -
2
The Edge Machine Learning library
Machine learning algorithms for edge devices
Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are... -
3
Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
4
DMTK
Microsoft Distributed Machine Learning Toolkit
...Developed by Microsoft Research, the toolkit provides infrastructure and algorithms designed to train large models efficiently on clusters of machines rather than a single system. At its core is a parameter-server architecture called Multiverso, which manages model parameters and synchronizes updates across distributed training processes. This architecture allows developers to build machine learning systems capable of processing massive datasets and training complex models with reduced infrastructure requirements. DMTK also includes several specialized algorithms and systems, such as LightLDA for large-scale topic modeling and distributed implementations of word embedding techniques used in natural language processing. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
GPU Machine Learning Library. This library aims to provide machine learning researchers and practitioners with a high performance library by taking advantage of the GPU enormous computational power. The library is developed in C++ and CUDA.
-
6
Bolt ML
10x faster matrix and vector operations
Bolt is an open-source research project focused on accelerating machine learning and data mining workloads through efficient vector compression and approximate computation techniques. The core idea behind Bolt is to compress large collections of dense numeric vectors and perform mathematical operations directly on the compressed representations instead of decompressing them first. This approach significantly reduces both memory usage and computational overhead when working with high-dimensional data commonly used in machine learning systems. ... -
7
libfastknn
Fast C++ KNN classifier
KNN Classifier library for C++, at background using armadillo. In k-NN classification, the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor. -
8
Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and... -
9
tiny-dnn
header only, dependency-free deep learning framework in C++14
tiny-dnn is a C++14 implementation of deep learning. It is suitable for deep learning on limited computational resources, embedded systems, and IoT devices. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
10
nunn
This is an implementation of a machine learning library in C++17
nunn is a collection of ML algorithms and related examples written in modern C++17. -
11
Freeware experimental artificial intellectual systems based on self-organization of chaotic digital network. The peculiarity of this system is that the digital network created using radionic* technology that provides interaction between human and computer thinking. This digital network of the brain obtained by the interaction of the operator with the software, on the basis of generating random sequences at pomotsi quark-neuronal cluster. Thus, in part, this artificial neural network is a...
-
12
node-opencv
OpenCV Bindings for node.js
OpenCV bindings for Node.js. OpenCV is the defacto computer vision library - by interfacing with it natively in node, we get powerful real time vision in js. People are using node-opencv to fly control quadrocoptors, detect faces from webcam images and annotate video streams. If you're using it for something cool, I'd love to hear about it! You'll need OpenCV 2.3.1 or newer installed before installing node-opencv. You can use opencv to read in image files. Supported formats are in the OpenCV... -
13
Multiple Back-Propagation (with CUDA)
Open source software for training neural networks
Multiple Back-Propagation is an open source software application for training neural networks with the backpropagation and the multiple back propagation algorithms. Currently this project is also hosted at http://code.google.com/p/multiplebackpropagation -
14
-
15
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.
-
16
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,...
-
17
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. -
18
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. -
19
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.
-
20
Virtual Eyewear
An eyewear trying simulator
Try this software and find out the eyewear style that is the most suitable for you. -
21
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! -
22
Speech recognition research toolkit
-
23
Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation... -
24
Accelerated Feature Extraction Tool
A fast GPU accelerated feature extraction software for speech analysis
A fast feature extraction software tool for speech analysis and processing. It incorporates standard MFCC, PLP, and TRAPS features. The tool is a specially designed to process very large audio data sets. It uses GPU acceleration if compatible GPU available (CUDA as weel as OpenCL, NVIDIA, AMD, and Intel GPUs are supported). CPU SSE intrinsic instruction set is used in cases where no compatible GPU present. The output files are stored in HTK format. The software is developed at Department of... -
25
Automatic cell lineage reconstruction
Automatic segmentation and tracking for 3D time-lapse microscopy
From Amat et al., Nature Methods, 2014*: "The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (1) generality, by reconstructing cell lineages in four-dimensional, terabyte-sized image data of fruit-fly, zebrafish and mouse embryos, acquired with three different types of...
