Search Results for "frameworks" - Page 3

...The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch and TensorFlow. These models are widely used in artificial intelligence to generate new data that resembles the training data, such as images, text, or other structured outputs. The repository serves as an educational and experimental environment where users can study how generative models work internally and replicate results from academic research papers.

When to use TensorFlowSharp is a .NET binding for the TensorFlow machine learning framework that allows developers to run TensorFlow models directly from C# and other .NET languages. The project exposes TensorFlow’s native C API through a strongly typed interface designed to integrate naturally with the .NET ecosystem. Its primary purpose is to enable developers working in Microsoft-based environments to load trained TensorFlow models and perform inference or additional training within .NET...

The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit:...

...The library provides tools for retrieving financial time series data, preprocessing market data, and training predictive models that estimate future price movements. bulbea integrates common machine learning frameworks such as TensorFlow and Keras to build neural network models capable of learning patterns in historical financial data. It includes utilities for splitting datasets, normalizing time series, and training models such as recurrent neural networks that can capture temporal dependencies in market behavior. The library also incorporates sentiment analysis capabilities that analyze social media data, particularly from Twitter, to estimate public sentiment toward financial assets.

JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types...

This work is part of the area of Artificial Intelligence, in particular in the field of machine learning. The web service is built to facilitate the use of JCLAL in applications developed in any programming language. Users should know only the basic format to send and receive requests.

JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project.

...It also includes references to frameworks, model implementations, and related research projects across various machine learning subfields. The project acts as a directory of resources that can guide learners toward useful tools and documentation in the AI domain.

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.