Search Results for "learn"
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Showing 24 open source projects for "learn"
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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.
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
...The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation. -
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Tribuo
Tribuo - A Java machine learning library
...It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts you're using in production. Tribuo's Models, Datasets, and Evaluations have provenance, meaning they know exactly what parameters, transformations, and files were used to create them. Provenance data allows each model to be rebuilt verbatim from scratch and for evaluations to track the models and datasets used for each experiment. -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
...DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your favorite IDE to build, train, and deploy your models. DJL makes it easy to integrate these models with your Java applications. Because DJL is deep learning engine agnostic, you don't have to make a choice between engines when creating your projects. You can switch engines at any point. ... -
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PC_Workman_HCK
AI-powered PC monitoring that explains. Not shows numbers/spikes.
PC_Workman is what 680 hours of coding after warehouse shifts looks like. Built on a laptop hitting 94°C, this AI-powered monitoring tool does what Task Manager can't: it understands your system, not just measures it. Features: - Time travel monitoring - debug issues from hours ago - AI diagnostics with HCK_GPT - Custom fan curves with profiles - Floating always-on-top widget - 2D system map - Cross-GPU support (NVIDIA/AMD/Intel) Four complete rebuilds. 29 features killed.... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Next Generation Programming
Compose Software Without Writing Any Programing Code
...Programmers can use the software to compose of simple/complex applications : Database programs, circuit design, generate code and upload to chip for designed circuits (ESP8266, ESP32 chips) The Software in question is much simpler to use than PWCT (https://sourceforge.net/projects/doublesvsoop/) software. The Software has more features than PWCT software such as SCADA. Please start by looking at examples from the website first. In this way, you can learn the features of the software and how to use the software in a very short time. More Information (Documents, Videos, Examples ...) : negep.epizy.com -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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BioC
We describe a simple XML format to share text documents and annotation
... - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining. -
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Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
OCL stands for Open Cezeri Library (yet another linear algebra and matrix library). This library provides rapid coding as matlab ease of use. To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. ... -
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libVMR
VMR - machine learning library
...libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification). -
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DL-Learner is a tool for learning concepts in Description Logics (DLs) from user-provided examples. Equivalently, it can be used to learn classes in OWL ontologies from selected objects. As of August 2014, the source code management of DL-Learner has moved to Github: https://github.com/AKSW/DL-Learner Please use this for the latest code and issue tracking and the website (http://dl-learner.org) for general information.
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JConstraints
Java Framework to implement solutions to solve constraints problems
...Just to name a few algorithms, the Framework can solve any constraints problems using: - Regular Backtracking; - A variety of Backjumping algorithms; - A variety of arc-consistency algorithms; - Local search algorithm; - Tabu search algorithm; - Maximize solutions: comming soon; - Minimize solutions: comming soon; The Framework also enables heuristic injections so that the developers can achieve greater performance of algorithms using their own heuristics. Version 1.0: Released! Version 1.1: Coming soon See the tutorial in the Wiki page to learn how to use this Framework. -
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Sentence Composer
Compose the writings semi-automatically
...Transduction, or transductive inference, tries to predict new outputs on specific and fixed (test) cases from observed, specific (training) cases. The simplest realization for transductive inference is the method of k-nearest neighbors. Learning to learn learns its own inductive bias based on previous experience. ...AND SO ON.... Enjoy the program ! -
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Ms. Pac-Man Framework
Using reinforcement learning with relative input to train Ms. Pac-Man
This Java-application contains all required components to simulate a game of Ms. Pac-Man and let an agent learn intelligent playing behaviour using reinforcement learning and either Q-Learning or SARSA. The framework was developed by Luuk Bom and Ruud Henken, under supervision of Marco Wiering, Department of Artificial Intelligence, University of Groningen. It formed the basis of a bachelor's thesis titled "Using reinforcement learning with relative input to train Ms. -
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This project develops a web-based (JSP) Fuzzy Rule-Based Expert System for analyzing ECG (electro cardio gram) signals & diagnosing Tachi-Arrhythmias. Proj. main blocks: inference engine, knowledgebase, KB editor, explanation, and feature extraction.
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RASCALLI stands for "Responsive Artificial Situated Cognitive Agents that Live and Learn on the Internet". The primary goal is to develop software agents that assist their users in finding relevant information on the Internet.
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IReNNS (Indipendent Recurrent Neural Network for Structures) is a recursive self-organizing neural network able to learn scalar functions on graphs. Derived from Cascade-Correlation. Developed by Antonino Trovato at Politecnico di Milano.
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TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.
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A learning package for children, helping them to learn a foreign language. Techniques such as speech recognition will be used.
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Project Genesis brings the game of life up-to-date. instead of dots, we have animals, instead of trivial rules about close proximity dots, we model real world activities: move,eat,kill,steal,destroy,sleep, breed and learn different patterns of behavior.
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An agent that tries to learn your taste in music based on an example database, using different AI-learning-approaches.
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Freality Machine Intelligence (FMI), is a Machine Intelligence architecture that will allow a machine to learn general information about, and interact with its world, esp. the Freality Metaverse (FMC).
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This project is for automatically rotating images based on content. This was a masters project and contains simple implementations of machine learning algorithms.
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