Showing 45 open source projects for "simple software manager"

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  • 1
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    ...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, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour).
    Downloads: 3 This Week
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  • 2
    AlphaZero.jl

    AlphaZero.jl

    A generic, simple and fast implementation of Deepmind's AlphaZero

    Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
    Downloads: 9 This Week
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  • 3
    Haiku

    Haiku

    JAX-based neural network library

    Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used...
    Downloads: 0 This Week
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  • 4
    dm_control

    dm_control

    DeepMind's software stack for physics-based simulation

    DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based).
    Downloads: 3 This Week
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  • 5
    libvips

    libvips

    A fast image processing library with low memory needs

    libvips is a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good...
    Downloads: 5 This Week
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  • 6
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared...
    Downloads: 4 This Week
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  • 7
    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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  • 8
    Ray

    Ray

    A unified framework for scalable computing

    Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best...
    Downloads: 2 This Week
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  • 9
    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. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the...
    Downloads: 0 This Week
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  • 10
    Avalanche

    Avalanche

    End-to-End Library for Continual Learning based on PyTorch

    Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major...
    Downloads: 0 This Week
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  • 11
    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. We have outsourced a lot of...
    Downloads: 0 This Week
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  • 12
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,...
    Downloads: 0 This Week
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  • 13
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that...
    Downloads: 0 This Week
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  • 14
    Deep Java Library (DJL)

    Deep Java Library (DJL)

    An engine-agnostic deep learning framework in Java

    Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. 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...
    Downloads: 0 This Week
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  • 15
    PySyft

    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...
    Downloads: 0 This Week
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  • 16
    Semantra

    Semantra

    Multi-tool for semantic search

    Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. ...
    Downloads: 1 This Week
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  • 17
    PoseidonQ  - AI/ML Based QSAR Modeling

    PoseidonQ - AI/ML Based QSAR Modeling

    ML based QSAR Modelling And Translation of Model to Deployable WebApps

    - This Software was made with an intention to make QSAR/QSPR development more efficient and reproducible. - Published in ACS, Journal of Chemical Information and Modeling . Link : https://pubs.acs.org/doi/10.1021/acs.jcim.4c02372 - Simple to use and no compromise on essential features necessary to make reliable QSAR models. - From Generating Reliable ML Based QSAR Models to Developing Your Own QSAR WebApp.
    Downloads: 13 This Week
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  • 18
    Django friendly finite state machine

    Django friendly finite state machine

    Django friendly finite state machine support

    Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a...
    Downloads: 0 This Week
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  • 19
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already...
    Downloads: 0 This Week
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  • 20
    KotlinDL

    KotlinDL

    High-level Deep Learning Framework written in Kotlin

    KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning...
    Downloads: 0 This Week
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  • 21
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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  • 22
    Captcha Server

    Captcha Server

    A fast and stable captcha auto solving server with API.

    ...Earn money from customers who wants to auto solve captchas? This is it.. Make a website and an API interface and integrate the Captcha Server API, walla.. a new business! We Provide A+ Captcha Solving Software For Better Captcha Solving Business. Launch Captcha Server from any Windows OS servers and set the server IP and Port to make it available to endusers and developers alike. Captcha Server has a very simple and straight forward API using the 2captcha.com API format. API is easy to fork and develop your own captcha business. ...
    Downloads: 0 This Week
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  • 23
    LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
    Downloads: 0 This Week
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  • 24
    ManimML

    ManimML

    ManimML is a project focused on providing animations

    ManimML is a project focused on providing animations and visualizations of common machine-learning concepts with the Manim Community Library. Please check out our paper. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine-learning concepts. Additionally, we want to provide a set of abstractions that allow users to focus on explanations instead of software engineering.
    Downloads: 0 This Week
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  • 25
    UnionML

    UnionML

    Build and deploy machine learning microservices

    Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine...
    Downloads: 0 This Week
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