Search Results for "learning system" - Page 4
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Showing 192 open source projects for "learning system"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. OWL (Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation) is an advanced framework designed to enhance multi-agent collaboration, improving task automation across various domains. By utilizing dynamic agent interactions, OWL aims to streamline and optimize complex workflows, making AI collaboration more natural, efficient, and adaptable. It is built on... -
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Astrape
Optical-packet node transceiver frequency allocation
In an optical network scenario which consists of multiple nodes (whiteboxes) at its edges and ROADMs in-between, the coherent transceiver average laser configuration time is improved. The process is evaluated according to a testbed setup. This is facilitated in the appropriate lab equipment (or via simulation when required). For that purpose, a software agent (Netconf server) residing at the whiteboxes, is developed receiving input from the Software-Defined Networking (SDN) packet... -
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SynaptaOS
Synapta OS is a preconfigured educational Linux distribution with AI
🌐 Synapta OS Synapta OS is an educational Linux distribution preconfigured with local Artificial Intelligence (AI) capabilities. It is designed for schools and remote areas where Internet connectivity is limited or unavailable, offering access to AI-based learning and digital tools offline. Version 1.4.6 -
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Auto_Img_Renamer
AutoimgRenamer is a Python tool to rename image files in a folder.
AutoimgRenamer is a lightweight Python tool that automatically renames all image files in a selected folder using a specified base name and an incremental index. It’s especially useful for organizing datasets, preparing files for machine learning, or batch-renaming personal image collections. Features 1. Rename .jpg, .jpeg, .png, .gif, .bmp, and .webp images 2. Simple, fast, and efficient 3. Customizable base name for files How It Works The tool scans the selected folder, finds all... -
Lightspeed golf course management softwareFrom tee sheet management, point of sale and payment processing to marketing, automation, reporting and more—Lightspeed is built for the pro shop, restaurant, back office, beverage cart and beyond.
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Hack Snapchat Account with AI
AI-driven Snapchat account security hacking
Hack Snapchat Password - AI-Powered Tool This application was made using the API of PASS REVELATOR, for more information about Snapchat hacking account and security, please visit their website: https://www.passwordrevelator.net/en/passdecoder Advanced Security Assessment Platform for Instagram A machine learning-based system designed to hack and demonstrate password vulnerability through controlled, authorized simulations. It employs sophisticated pattern analysis to audit security robustness. CORE FUNCTIONALITIES: • Algorithmic Credential Simulation - Uses predictive models rather than traditional dictionaries • Predictive Pattern Analysis - Neural network systems for intelligent security testing • Contextual Evaluation - Examines metadata for relevant credential variations • Progressive Assessment Methodology - Layered approach from basic to complex patterns • Privacy-Preserving Architecture - Integrated anonymity protocols and proxy systems • Live Analysis Dashboard -
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UtilityHub
UtilityHub is a lightweight, all-in-one desktop utility.
...Built with a focus on speed, simplicity, and a clean dark-themed interface, UtilityHub bundles multiple essential tools into a single user-friendly application. User Interface • Clean & Intuitive GUI • Dark Theme for comfortable long-duration usage • Beginner-friendly design with minimal learning curve Technology Stack • Python • Tkinter (GUI) • SQLite (Local Storage) • Pillow / PDF Libraries • Packaged as a standalone Windows EXE System Requirements • Operating System: Windows 7 / 8 / 10 / 11 • No Internet Required • No External Dependencies ________________________________________ Installation 1. Download UtilityHub.exe 2. ... -
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Flashcard App
This is an app that will help you learn and prosper in any subject!
A lightweight but effective Flashcard based learning app to study and memorize using a reward system, built using python and the customtkinter library. Here you can create flashcards and quiz yourself on any topic you like, save the flashcards for later use or simply import one with the correct format. Give yourself hints, earn points and have fun! Play quiz with your friends see who gets the most points. -
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Liveliness and Face Identification
Leading free and open-source liveliness check &face recognition system
...If user's pic is in DB, it will show the matching name or else you can upload your pic with name to do detection. Application has many uses like door lock, attendance system or any similar identification usages. Face Recognition is highly accurate and simplest application -
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BashCore
A custom Debian live ISO with security tools, no GUI, only Bash.
BashCore is a Debian-based live ISO for security pros, networking enthusiasts, and students. Minimalist and GUI-free, it relies entirely on Bash. Lightweight, fast, GPU-ready, and now offering an optional PREEMPT_RT kernel, it provides a fresh environment on every boot, ideal for safe experimentation, learning, and diagnostics. Built with Debian live-build, MIT-licensed, no branding, telemetry, or tracking. Also available: BashCoreX adds XFCE with Firefox, Tor & Mullvad browsers,... -
Inventors: Validate Your Idea, Protect It and Gain Market AdvantagessenseIP is an AI innovation platform for inventors, automating any aspect of IP from the moment you have an idea. You can have it researched for uniqueness and protected; quickly and effortlessly, without expensive attorneys. Built for business success while securing your competitive edge.
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Dosidicus
Tamagotchi-style digital pet with a neural network that can learn
...The squid makes autonomous decisions based on current state (hunger, sleepiness, etc.). Implements a vision cone for food detection, simulating realistic foraging behavior. Hebbian learning algorithm runs every 30 seconds (configurable) Experiences from short-term and long-term memory can influence decision-making Squid can create new neurons in response to his environment (Neurogenesis) Design your own squid brain with GUI tools! Needs Management System: Tracks various needs like hunger, sleepiness, happiness, and cleanliness. ... -
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CoTracker
CoTracker is a model for tracking any point (pixel) on a video
CoTracker is a learning-based point tracking system that jointly follows many user-specified points across a video, rather than tracking each point independently. By reasoning about all tracks together, it can maintain temporal consistency, handle mutual occlusions, and reduce identity swaps when trajectories cross. The model takes sparse point queries on one frame and predicts their sub-pixel locations and a visibility score for every subsequent frame, producing long, coherent trajectories. ... -
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Asteroid
The PyTorch-based audio source separation toolkit for researchers
The PyTorch-based audio source separation toolkit for researchers. Pytorch-based audio source separation toolkit that enables fast experimentation on common datasets. It comes with a source code thats supports a large range of datasets and architectures, and a set of recipes to reproduce some important papers. Building blocks are thought and designed to be seamlessly plugged together. Filterbanks, encoders, maskers, decoders and losses are all common building blocks that can be combined in a... -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. ... -
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NuPIC
Numenta platform for intelligent computing
The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see numenta.org or the NuPIC Forum. If you want... -
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OpenNMT-tf
Neural machine translation and sequence learning using TensorFlow
OpenNMT is an open-source ecosystem for neural machine translation and neural sequence learning. OpenNMT-tf is a general-purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support sequence-to-sequence mapping, sequence tagging, sequence classification, language modeling. Models are described with code to allow training custom architectures and overriding default behavior. For example, the... -
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Detic
Code release for "Detecting Twenty-thousand Classes
Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories without exhaustive box annotations. The system supports zero- or few-shot extension to novel categories via semantic embeddings and class name supervision, making “open-world” detection practical. ... -
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MMClassification
OpenMMLab Image Classification Toolbox and Benchmark
MMClassification is an open-source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. Supports DenseNet, VAN and PoolFormer, and provide pre-trained models. Supports training on IPU. Supports a series of CSP networks, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or... -
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Spektral
Graph Neural Networks with Keras and Tensorflow 2
Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for... -
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TensorFlow Documentation
TensorFlow documentation
An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples. -
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SageMaker Experiments Python SDK
Experiment tracking and metric logging for Amazon SageMaker notebooks
Experiment tracking in SageMaker Training Jobs, Processing Jobs, and Notebooks. SageMaker Experiments is an AWS service for tracking machine learning Experiments. The SageMaker Experiments Python SDK is a high-level interface to this service that helps you track Experiment information using Python. Experiment tracking powers the machine learning integrated development environment Amazon SageMaker Studio. Experiment: A collection of related Trials. Add Trials to an Experiment that you wish to... -
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VALL-E
PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)
...During the pre-training stage, we scale up the TTS training data to 60K hours of English speech which is hundreds of times larger than existing systems. VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as an acoustic prompt. Experiment results show that VALL-E significantly outperforms the state-of-the-art zero-shot TTS system in terms of speech naturalness and speaker similarity. In addition, we find VALL-E could preserve the speaker's emotion and acoustic environment of the acoustic prompt in synthesis. -
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FFCV
Fast Forward Computer Vision (and other ML workloads!)
ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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auto-sklearn
Automated machine learning with scikit-learn
auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system. auto-sklearn 2.0 works the same way as regular auto-sklearn. auto-sklearn is licensed the same way as scikit-learn, namely the 3-clause BSD license. -
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PySC2
StarCraft II learning environment
PySC2 is DeepMind's Python component of the StarCraft II Learning Environment (SC2LE). It exposes Blizzard Entertainment's StarCraft II Machine Learning API as a Python RL Environment. This is a collaboration between DeepMind and Blizzard to develop StarCraft II into a rich environment for RL research. PySC2 provides an interface for RL agents to interact with StarCraft 2, getting observations and sending actions.
