Showing 165 open source projects for "learning classifier system"

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    Build Agents and Models on One Platform

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  • 1
    System Design

    System Design

    Learn how to design systems and prepare for system design interviews

    This project is an open, course-style repository designed to help you learn system design from fundamentals through advanced, interview-ready thinking. It organizes core networking and distributed-systems concepts into a structured path, so you can build intuition before jumping into “design X” exercises. It covers the building blocks that show up in real architectures, such as DNS, load balancing, caching, CDNs, proxies, scalability and availability tradeoffs, and storage patterns, then connects those pieces to larger system goals. ...
    Downloads: 3 This Week
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  • 2
    System Design Primer

    System Design Primer

    Learn how to design large-scale systems

    ...The repository also contains study guides for short, medium, and long interview timelines, allowing learners to focus on both breadth and depth depending on their preparation needs. In addition, it includes flashcard decks designed to reinforce learning through spaced repetition, making it easier to retain key system design knowledge.
    Downloads: 3 This Week
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  • 3
    Imagen - Pytorch

    Imagen - Pytorch

    Implementation of Imagen, Google's Text-to-Image Neural Network

    Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
    Downloads: 0 This Week
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  • 4
    Volcano

    Volcano

    A Cloud Native Batch System (Project under CNCF)

    Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with.
    Downloads: 260 This Week
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    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 5
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,...
    Downloads: 3 This Week
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  • 6
    mlpack

    mlpack

    mlpack: a scalable C++ machine learning library

    mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings.
    Downloads: 0 This Week
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  • 7
    AutoKeras

    AutoKeras

    AutoML library for deep learning

    AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0.
    Downloads: 0 This Week
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  • 8
    dlib

    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.
    Downloads: 8 This Week
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  • 9
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds.
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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    MongoDB 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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  • 10
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,...
    Downloads: 0 This Week
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  • 11
    CodeGuide

    CodeGuide

    This repository is a collection of the author, Xiao Fuge

    ...It also functions as a guide for both junior developers who want to grow into architects and experienced engineers who seek deeper mastery of system design. By combining educational material with hands-on examples, CodeGuide bridges the gap between theoretical learning and practical application in enterprise-level Java development.
    Downloads: 3 This Week
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  • 12
    Zstandard

    Zstandard

    Zstandard - Fast real-time compression algorithm

    Zstandard is a fast compression algorithm, providing high compression ratios. It also offers a special mode for small data, called dictionary compression. The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. Its format is stable and published as IETF RFC 8478. The negative compression levels, specified with --fast=#, offer...
    Downloads: 69 This Week
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  • 13
    Swift Macros

    Swift Macros

    A curated list of awesome Swift Macros

    ...It is especially valuable for developers moving from code-generation tools toward Swift’s built-in macro system. Swift-Macros is not a single library, but a reference hub for learning the Swift macro ecosystem and finding useful implementation patterns.
    Downloads: 1 This Week
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  • 14
    zvt

    zvt

    Modular quant framework

    For practical trading, a complex algorithm is fragile, a complex algorithm building on a complex facility is more fragile, complex algorithm building on a complex facility by a complex team is more and more fragile. zvt wants to provide a simple facility for building a straightforward algorithm. Technologies come and technologies go, but market insight is forever. Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt....
    Downloads: 1 This Week
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  • 15
    XGBoost

    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....
    Downloads: 6 This Week
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  • 16
    DVC

    DVC

    Data Version Control | Git for Data & Models

    DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,...
    Downloads: 0 This Week
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  • 17
    RA.Aid

    RA.Aid

    Develop software autonomously

    RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality.​
    Downloads: 0 This Week
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  • 18
    IIAB

    IIAB

    Internet-in-a-Box, build your own library of Alexandria

    Internet-in-a-Box (IIAB) is a “learning hotspot” that brings the Internet's crown jewels (Wikipedia in any language, thousands of Khan Academy videos, zoomable OpenStreetMap, electronic books, WordPress journaling, “Toys from Trash” electronics projects, etc.) to those without Internet. You can build your own tiny, affordable server (an offline digital library) for your school, your medical clinic, your prison, your region, and/or your very own family, accessible with any nearby smartphone,...
    Downloads: 0 This Week
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  • 19
    My Python Eggs

    My Python Eggs

    Python Examples

    ...Rather than being a single cohesive application, it functions as a repository of utilities that demonstrate how Python can be used to solve everyday problems and automate repetitive tasks. The scripts cover a wide range of topics, including file management, networking, system monitoring, web scraping, and even simple games, making it a versatile learning resource. Many of the programs are designed to reduce manual workload by automating tasks such as renaming files, scanning directories, or checking system information. The repository also includes examples of more advanced concepts like multithreading, API interaction, and GUI development, providing a gradual learning curve for beginners.
    Downloads: 0 This Week
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  • 20
    NFH Self-Improvement Loop

    NFH Self-Improvement Loop

    Minimal adversarial framework for AI agent self-modification

    NFH Self-Improvement Loop is a conceptual framework and implementation designed to model continuous self-improvement cycles using AI systems. It focuses on creating feedback loops where outputs are evaluated, refined, and reintroduced into the system for further improvement. The project emphasizes iterative learning, allowing systems to evolve over time through repeated evaluation and adjustment. It can be applied to areas such as content generation, decision-making, and personal productivity systems. The framework encourages structured reflection and optimization, ensuring that each iteration builds upon previous results. ...
    Downloads: 0 This Week
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  • 21
    RecBole

    RecBole

    A unified, comprehensive and efficient recommendation library

    A unified, comprehensive and efficient recommendation library. We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. RecBole is developed based on Python and PyTorch for...
    Downloads: 0 This Week
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  • 22
    EpicReact.Dev

    EpicReact.Dev

    Build a ReactJS App workshop

    ...The project demonstrates how to structure a modern React app, including data modeling, authentication, routing, testing, and interaction with a backend. It uses a realistic “bookshelf” domain where users can manage lists of books, track reading status, and record notes, which provides a concrete context for learning. The repository includes setup scripts and system requirements checks for Git, Node, and npm, plus Docker and Codespaces options for people who struggle with local environments. A guided workflow, driven by a node go script and INSTRUCTIONS.md, lets learners move between exercises and extra credit steps while the repository updates the working files for each stage. ...
    Downloads: 2 This Week
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  • 23
    Professional Programming

    Professional Programming

    A collection of learning resources for curious software engineers

    Professional Programming is a long-running, curated collection of learning resources aimed at helping software engineers grow into well-rounded professionals. It goes far beyond basic “learn to code” material and covers topics like system design, debugging, testing, performance, security, architecture, and software craftsmanship. The list is organized by themes such as coding, design, operations, communication, and career, making it easy to dive into specific aspects of engineering practice. ...
    Downloads: 4 This Week
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  • 24
    spacy-transformers

    spacy-transformers

    Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

    spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any...
    Downloads: 0 This Week
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  • 25
    BotSharp

    BotSharp

    AI Multi-Agent Framework in .NET

    ...Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. It's written in C# running on .Net Core that is full cross-platform framework. C# is a enterprise-grade programming language which is widely used to code business logic in information management-related system.
    Downloads: 0 This Week
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