Search Results for "machine"
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74 projects for "machine" with 2 filters applied:
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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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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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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. -
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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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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. -
Build AI Apps with Gemini 3 on Vertex AIVertex AI gives developers access to Gemini 3—Google’s most advanced reasoning and coding model—plus 200+ foundation models including Claude, Llama, and Gemma. Build generative AI apps with Vertex AI Studio, customize with fine-tuning, and deploy to production with enterprise-grade MLOps. New customers get $300 in free credits.
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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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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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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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Laravel Dusk
Laravel Dusk provides simple end-to-end testing and browser automation
Laravel Dusk provides an expressive, easy-to-use browser automation and testing API. By default, Dusk does not require you to install JDK or Selenium on your machine. Instead, Dusk uses a standalone Chromedriver. However, you are free to utilize any other Selenium driver you wish. -
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Spin
Replicate your production environment locally using Docker
Stop wasting time fixing production issues you've already solved. Spin is a bash utility that improves the user experience for teams using Docker. Replicate any environment on any machine, regardless if they are running MacOS, Windows, or Linux. Centralize your infrastructure from a single configuration file using Docker. Spin is a wrapper script that dramatically improves the developer experience when working with Docker. Spin uses officially supported features and best practices from Docker. Spin connects proven open source technologies to give you the best developer experience to maintain your own, simplified stack. -
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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Laravel Installer
The Laravel application installer
...However, we believe Laravel is the best choice for building modern, full-stack web applications. Before creating your first Laravel project, make sure that your local machine has PHP and Composer installed. If you are developing on macOS or Windows, PHP and Composer can be installed in minutes via Laravel Herd. In addition, we recommend installing Node and NPM. -
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Netcap
A framework for secure and scalable network traffic analysis
The Netcap (NETwork CAPture) framework efficiently converts a stream of network packets into platform-neutral type-safe structured audit records that represent specific protocols or custom abstractions. These audit records can be stored on disk or exchanged over the network, and are well-suited as a data source for machine learning algorithms. Since parsing of untrusted input can be dangerous and network data is potentially malicious, a programming language that provides a garbage-collected memory-safe runtime is used for the implementation. -
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Argo Workflows
Workflow engine for Kubernetes
...Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. Argo Workflows is the most popular workflow execution engine for Kubernetes. It can run 1000s of workflows a day, each with 1000s of concurrent tasks. ... -
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Apache Flink
Stream processing framework with powerful stream
...Developers program against high-level APIs—DataStream and Table/SQL—to express transformations, joins, and stateful patterns, while specialized libraries support CEP, machine learning workflows, and connectors. A rich connector ecosystem integrates with systems like Kafka, Kinesis, filesystems, JDBC sources/sinks, and object stores. Deployments span Kubernetes, YARN, Mesos, and standalone clusters, and operational features such as savepoints, state backends, and metrics make long-running jobs manageable in production. -
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FluentDocker
Use docker, docker-compose local and remote in tests
This library enables docker and docker-compose interactions using a Fluent API. It is supported on Linux, Windows, and Mac. It also has support for the legazy docker-machine interactions. The fluent API builds up one or more services. Each service may be composite or singular. Therefore it is possible to e.g. fire up several docker-compose-based services and manage each of them as a single service or dig in and use all underlying services on each docker-compose service. -
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
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Optuna
A hyperparameter optimization framework
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API. Thanks to our define-by-run API, the code written with Optuna enjoys high modularity, and the user of Optuna can dynamically construct the search spaces for the hyperparameters. Optuna Dashboard is a real-time web dashboard for Optuna. You can check the optimization history, hyperparameter importances, etc. in graphs and tables. ... -
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PowerHub
A post exploitation tool based on a web application
...Authentication and remoting are handled idiomatically via PowerShell remoting or credential stores, enabling both interactive and scheduled runs. Built-in reporting features aggregate results into human-readable summaries and machine-friendly outputs (CSV/JSON) for pipeline consumption or ticketing integration. -
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KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
...It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image recognition, event processing, and other high-level applications to the Edge. With business logic running at the Edge, much larger volumes of data can be secured & processed locally where the data is produced. With data processed at the Edge, the responsiveness is increased dramatically and data privacy is protected. -
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Workerman
An asynchronous event driven PHP socket framework
...It has many high-performance components such as asynchronous Mysql, asynchronous Redis, asynchronous Http, MQTT Internet of Things client, and asynchronous message queue. Based on the high-performance Epoll event network library, a single machine can support millions of concurrent connections, with a long connection throughput of up to 36W/S. Objects such as PHP database can be resident in memory, reducing analysis and compilation and network overhead. -
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stkpp
C++ Statistical ToolKit
STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template... -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. -
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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... -
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Lumen PHP Framework
The Laravel Lumen Framework.
Laravel Lumen is a stunningly fast PHP micro-framework for building web applications with expressive, elegant syntax. We believe development must be an enjoyable, creative experience to be truly fulfilling. 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. -
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UnionML
Build and deploy machine learning microservices
...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 learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. ... -
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Kore
Scalable and secure web application framework
...It is fully privileged separated while using strong security features at the operating system level such as second, pledge, unveil, and more. Today Kore is used in a variety of applications ranging from high assurance cryptographic military devices, machine-learning stacks and even in the aerospace industry. From embedded platforms all the way to high-performance servers. Kore scales. Kore is open source software licensed under the ISC license and developed in my spare time. If Kore helped you or your company please consider a donation to help any future development. Kore provides official docker images for its releases.
