Search Results for "perceptron c"
Sort By:
Showing 15 open source projects for "perceptron c"
View related business solutions-
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
1
Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared... -
2
Neural Networks Collection
Neural Networks Collection
This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
3
Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
4
Machine Learning:Perceptron
Minimal version of the perceptron algorithm.Coded the simpler way.
A minimal version of the perceptron algorithm is implemented in C#. Coded for ease of understanding the referred to algorithm. Enter your info-press the learn button-then type in new info which the program will try and recognnise. There are some typos in the text displayed-but the code is correct. -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
5
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. -
6
The MaxParser is written in c++ and can parse with first, second, third and fourth order projective Graph-based Dependency parsing algorithm. The project is the new version of the project "Max-MSTParser". If you want to use this software for research, please reference this web address in your papers
-
7
bnns
Research tool for interactive training of artificial neural networks.
BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data. -
8
DropoutMLP
A Multi-Layer Perceptron with Dropout
This project was derived from the following project on CCodeChamp by MR CODER. http://www.ccodechamp.com/c-program-of-multilayer-perceptron-net-using-backpropagation/ I rewrote the project in C++ and and made it more object oriented. Then, I added the capability to use dropout on the hidden layers as specified by Geoffrey Hinton et. al. in "Improving neural networks by preventing co-adaptation of feature detectors" (2012). http://www.cs.toronto.edu/~hinton/absps/dropout.pdf I found that it performed much worse with dropout. ... -
9
Featurama is a library that implements various sequence-labeling algorithms. Currently Michael Collins' averaged perceptron algorithm is fully implemented.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
10
TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.
-
11
tiny-AI Library
small and fast C++ library dealing with artificial intelligence
A fast artificial intelligence library which currently supports: kNN (k-Nearest Neighbor algorithm) MLP (Multilayer-Perceptron) -
12
Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
-
13
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.
-
14
ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.
-
15
Neural network library for C++ applications in Windows and Linux. Multi-Layer perceptron, radial-basis function networks and Hopfield networks are supported. You can interface this with Matlab's Neural Network Toolbox using the Matlab Extensions Pack
- Previous
- You're on page 1
- Next
