Search Results for "machine"
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Showing 197 open source projects for "machine"
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Cut Cloud Costs with Google Compute EngineSave on compute costs with Compute Engine. Reduce your batch jobs and workload bill 60-91% with Spot VMs. Compute Engine's committed use offers customers up to 70% savings through sustained use discounts. Plus, you get one free e2-micro VM monthly and $300 credit to start.
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Go from Data Warehouse to Data and AI platform with BigQueryBigQuery is more than a data warehouse—it's an autonomous data-to-AI platform. Use familiar SQL to train ML models, run time-series forecasts, and generate AI-powered insights with native Gemini integration. Built-in agents handle data engineering and data science workflows automatically. Get $300 in free credit, query 1 TB, and store 10 GB free monthly.
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Slack Machine
A simple, yet powerful and extendable Slack bot
Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly but also allows for easy code organization. A plugin can look as simple as this: -
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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... -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. ... -
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FSM for Go
Finite State Machine for Go
FSM is a finite state machine for Go. It is heavily based on two FSM implementations. Javascript Finite State Machine, and Fysom for Python. Visualize outputs a visualization of a FSM in Graphviz format. VisualizeForMermaidWithGraphType outputs a visualization of a FSM in Mermaid format as specified by the graphType. VisualizeWithType outputs a visualization of a FSM in the desired format. -
Managed MySQL, PostgreSQL, and SQL Databases on Google CloudCloud SQL is a fully managed relational database for MySQL, PostgreSQL, and SQL Server. We handle patching, backups, replication, encryption, and failover—so you can focus on your app. Migrate from on-prem or other clouds with free Database Migration Service. IDC found customers achieved 246% ROI. New customers get $300 in credits plus a 30-day free trial.
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Rasa
Open source machine learning framework to automate text conversations
Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. -
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Laravel Valet
A more enjoyable local development experience for Mac
...You can even share your sites publicly using local tunnels. Yeah, we like it too. Laravel Valet configures your Mac to always run Nginx in the background when your machine starts. Then, using DnsMasq, Valet proxies all requests on the *.test domain to point to sites installed on your local machine. In other words, a blazing-fast Laravel development environment that uses roughly 7 MB of RAM. Valet isn't a complete replacement for Vagrant or Homestead, but provides a great alternative if you want flexible basics, prefer extreme speed, or are working on a machine with a limited amount of RAM. -
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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 automates the process of building best performing models for your Machine Learning scenario. ... -
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Seldon Core
An MLOps framework to package, deploy, monitor and manage models
...Framework agnostic, supports top ML libraries, toolkits and languages. Advanced deployments with experiments, ensembles and transformers. Our open-source framework makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes. -
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MLJ
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. -
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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MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
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Flower
Flower: A Friendly Federated Learning Framework
...Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
...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 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. ... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an... -
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Kedro
A Python framework for creating reproducible, maintainable code
...Makes a seamless transition from development to production, as you can write quick, throw-away exploratory code and transition to maintainable, easy-to-share, code experiments quickly. Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code. -
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Ray
A unified framework for scalable computing
...Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core. -
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Spring Statemachine
Framework for application developers to use state machine concepts
The Spring Statemachine project aims to provide a common infrastructure to work with state machine concepts in Spring applications. It is advised to check the actual state of this project by referring to the latest releases found on the Spring Statemachine Project Page. The git repo default branch may be relatively unstable when new features are added to the source code. Spring Statemachine uses a Gradle-based build system. In the instructions below, . -
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Lumen Framework
The Laravel Lumen Framework
...Lumen attempts to take the pain out of development by easing common tasks used in the majority of web projects, such as routing, database abstraction, queueing, and caching. The Lumen framework has a few system requirements. Of course, all of these requirements are satisfied by the Laravel Homestead virtual machine, so it's highly recommended that you use Homestead as your local Lumen development environment. Lumen utilizes Composer to manage its dependencies. So, before using Lumen, make sure you have Composer installed on your machine. Since Lumen is a totally separate framework from Laravel, it does not intentionally offer compatibility with any additional Laravel libraries like Cashier, Passport, Scout, etc. -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
...It adheres to the core concept and architecture of static compilation and streaming parallelism and solves the memory wall challenge at the cluster level. world-leading level. Provides a variety of services from primary AI talent training to enterprise-level machine learning lifecycle integrated management (MLOps), including AI training and AI development, and supports three deployment modes of public cloud, private cloud and hybrid cloud. -
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MAME
MAME is a multi-purpose emulation framework
...The fact that the software is usable serves primarily to validate the accuracy of the documentation (how else can you prove that you have recreated the hardware faithfully?). Over time, MAME (originally stood for Multiple Arcade Machine Emulator) absorbed the sister-project MESS (Multi Emulator Super System), so MAME now documents a wide variety of (mostly vintage) computers, video game consoles and calculators, in addition to the arcade video games that were its initial focus. The MAME project as a whole is distributed under the terms of the GNU General Public License, 2 (GPL-2.0), since it contains code made available under multiple GPL-compatible licenses. -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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Urbit
An operating function
Urbit is a personal server stack built from scratch. It has an identity layer (Azimuth), virtual machine (Vere), and operating system (Arvo). A running Urbit "ship" is designed to operate with other ships peer-to-peer. Urbit is a general-purpose, peer-to-peer computer and network. Urbit is for everyone, but sometimes it is easy to get lost in this universe. It solves the hard problems of implementing a peer-to-peer network (including identity, NAT traversal, and exactly-once delivery) in the kernel so app developers can focus on business logic. ...
