Search Results for "learning classifier system"
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Showing 67 open source projects for "learning classifier system"
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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.
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative)... -
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dlib
Toolkit for making machine learning and data analysis applications
...No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. All operating system specific code is isolated inside the OS abstraction layers which are kept as small as possible. -
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XGBoost
Scalable and Flexible Gradient Boosting
XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems.... -
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.
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theByteBook
In-depth explanation of cloud native related technologies
theByteBook is a large open-source repository that publishes a comprehensive technical book focused on high-availability system design, modern cloud-native infrastructure, and foundational engineering concepts, serving as both a learning resource and architecture reference. The content covers deep dives into networking principles, container ecosystems, Kubernetes, service meshes, distributed systems, and SRE/DevOps practices, aiming to help practitioners build reliable, scalable, and cost-efficient systems. ... -
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claude-reflect
A self-learning system for Claude Code that captures corrections
claude-reflect is a self-learning enhancement system for Claude Code that captures user corrections, positive feedback, and preferences during interactive coding sessions and turns them into persistent knowledge that improves future responses. It watches what you correct Claude about — such as preferring a particular model, style, or workflow — and automatically queues those learnings, then lets you review and sync them back into configuration files like CLAUDE.md and agent definitions so Claude remembers them across sessions. ... -
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Elasticsearch
A Distributed RESTful Search Engine
Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types. -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the... -
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tika-python
Python binding to the Apache Tika™ REST services
A Python port of the Apache Tika library that makes Tika available using the Tika REST Server. This makes Apache Tika available as a Python library, installable via Setuptools, Pip and easy to install. To use this library, you need to have Java 7+ installed on your system as tika-python starts up the Tika REST server in the background. To get this working in a disconnected environment, download a tika server file (both tika-server.jar and tika-server.jar.md5, which can be found here) and set... -
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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ggplot2
An implementation of the Grammar of Graphics in R
ggplot2 is a system written in R for declaratively creating graphics. It is based on The Grammar of Graphics, which focuses on following a layered approach to describe and construct visualizations or graphics in a structured manner. With ggplot2 you simply provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it will take care of the rest. ggplot2 is over 10 years old and is used by hundreds of thousands of people all over the world for... -
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PySyft
Data science on data without acquiring a copy
Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data... -
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich... -
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Catalyst.jl
Chemical reaction network and systems biology interface
Catalyst.jl is a symbolic modeling package for analysis and high-performance simulation of chemical reaction networks. Catalyst defines symbolic ReactionSystems, which can be created programmatically or easily specified using Catalyst's domain-specific language (DSL). Leveraging ModelingToolkit and Symbolics.jl, Catalyst enables large-scale simulations through auto-vectorization and parallelism. Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy... -
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Luigi
Python module that helps you build complex pipelines of batch jobs
...You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. It also comes with file system abstractions for HDFS, and local files that ensures all file system operations are atomic. -
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memphis
Next-Generation Event Processing Platform
Memphis enables building modern queue-based applications that require large volumes of streamed and enriched data, modern protocols, zero ops, up to x9 faster development, up to x46 fewer costs, and significantly lower dev time for data-oriented developers and data engineers. Queues and brokers are a mission-critical component in the modern application architecture and should be highly available and stable as possible. Provide great performance while maintaining efficient resource... -
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Fondant
Production-ready data processing made easy and shareable
Fondant is a modular, pipeline-based framework designed to simplify the preparation of large-scale datasets for training machine learning models, especially foundation models. It offers an end-to-end system for ingesting raw data, applying transformations, filtering, and formatting outputs—all while remaining scalable and traceable. Fondant is designed with reproducibility in mind and supports containerized steps using Docker, making it easy to share and reuse data processing components. ... -
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UAVs Predictive Maintenance
Vibration-Based Structural Health Monitoring of UAVs
This study presents an integrated software application that enables vibration-based structural health monitoring within a closed-loop Product Lifecycle Management (PLM) framework. The system collects time-domain vibration data from UAV components during the pre-flight phase and applies deep learning architectures—including Gated Recurrent Units (GRUs), Long Short-Term Memory networks (LSTMs), and Convolutional Neural Networks (CNNs)—for accurate fault classification. Communication with the UAV is handled through the DroneKit-Python API, while RESTful APIs interface with the Aras Innovator PLM platform to automate data exchange and support predictive maintenance. ... -
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Kalshi-Quant-TeleBot
Kalshi Advanced Quantitative Trading Bot is an enterprise-grade
...This bot leverages advanced quantitative strategies, machine learning techniques, and real-time data analysis to identify profitable trading opportunities while maintaining robust risk management protocols. Built with a modular architecture, the system combines Python-based trading algorithms with a JavaScript Telegram bot interface for dynamic monitoring and interaction. The bot is designed to operate continuously, making data-driven decisions based on news sentiment analysis, statistical arbitrage opportunities -
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Premium Markets
Premium Markets is an automated financial technical analysis system.
...Full installation instructions can be found at http://www.premiummarkets.uk/html/swtui.html#Download . I would also like to bring to your attention that, in its advanced version, Premium Markets also provides a Forecast machine learning engine based on neural networks. See http://www.premiummarkets.uk/ for documentation and a workable demo of the trend forecast and prediction engine. -
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Ubix Linux
The Pocket Datalab
Ubix stands for Universal Business Intelligence Computing System. Ubix Linux is an open-source, Debian-based Linux distribution geared towards data acquisition, transformation, analysis and presentation. Ubix Linux purpose is to offer a tiny but versatile datalab. Ubix Linux is easily accessible, resource-efficient and completely portable on a simple USB key. Ubix Linux is a perfect toolset for learning data analysis and artificial intelligence basics on small to medium datasets. ... -
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DevStore
A microservices e-commerce reference application
A microservices e-commerce reference application built with ASP.NET 6. The EShopOnContainers is an awesome project, however the code has some "bad smells". We found it difficult to start learning/using EShopOnContainers compared to DevStore. We like to think of the DevStore as a simplified (but no less complex) version and written with more care in code and small details. We also focused only on the Web architecture with ASP.NET. -
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LinuxOffice360
A universal desktop operating system.
It is an operating system designed for small businesses and offices. Very nice to look at and simple to use, whether you come from Linux, Windows or Mac. Without unnecessary frills, it is equipped with all the necessary software to start working even live. You will find everything in the right place and above all where you expect it to be. The learning curve is lightning fast and you will be productive right away. -
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KubeOperator
An open source, lightweight Kubernetes distribution
KubeOperator is an open source, lightweight Kubernetes distribution focused on helping enterprises plan, deploy, and operate production-level K8s clusters. Compared with heavyweight PaaS platforms such as OpenShift, KubeOperator only focuses on solving one problem, which is to help enterprises plan (Day 0), deploy (Day 1), and operate (Day 2) production-level K8S clusters, and achieve the ultimate. Supports multiple computing, storage and networking scenarios. Integrate Ansible and... -
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e-Dokyumento
e-Dokyumento is web-based Document Management System (DMS)
e-Dokyumento is opensource web-based Document Management System (DMS) A Document Management which automates the basic office document workflow such as receiving, filing, routing, and approving through capturing (scanning), digitizing (OCR Reading), storing, tagging, and electronically routing and approving (e-signature) of electronic documents. # Demo : https://e-dokyumento.herokuapp.com/ https://edokyu.seillig.com/ (refer to Readme.md for the... -
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Face Mask Detection
Face Mask Detection system based on computer vision and deep learning
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. ...
