Search Results for "support vector machine" - Page 3
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Showing 419 open source projects for "support vector machine"
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Tribuo
Tribuo - A Java machine learning library
Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts... -
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MediaPipe
Cross-platform, customizable ML solutions for live and streaming media
MediaPipe offers open-source cross-platform, customizable ML solutions for live and streaming media. Provides segmentation masks for prominent humans in the scene. MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU... -
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QMD
mini cli search engine for your docs, knowledge bases, etc.
...Because the entire system runs on the user’s machine, privacy is preserved and there’s no risk of exposing sensitive content to outside providers. -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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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oneDNN
oneAPI Deep Neural Network Library (oneDNN)
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the... -
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Multipass
Multipass orchestrates virtual Ubuntu instances
Multipass is a lightweight VM manager for Linux, Windows and macOS. It's designed for developers who want a fresh Ubuntu environment with a single command. It uses KVM on Linux, Hyper-V on Windows and QEMU on macOS to run the VM with minimal overhead. It can also use VirtualBox on Windows and macOS. Multipass will fetch images for you and keep them up to date. Since it supports metadata for cloud-init, you can simulate a small cloud deployment on your laptop or workstation. -
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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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Kata Containers
Build a standard implementation of lightweight Virtual Machines (VMs)
Kata Containers is an open source container runtime, building lightweight virtual machines that seamlessly plug into the container ecosystem. Kata Containers is an open source community working to build a secure container runtime with lightweight virtual machines that feel and perform like containers, but provide stronger workload isolation using hardware virtualization technology as a second layer of defense. Since launching in December 2017, the community successfully merged the best parts... -
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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,... -
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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. With Spark Streaming... -
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Urbit
An operating function
...The entire OS is a single pure function that provides application developers with strong guarantees: automated persistence and memory management, repeatable builds, and support for hot code reloading. Urbit is a personal OS designed from scratch to run peer-to-peer applications. A clean-slate OS and network for the 21st century. -
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NASM
A cross-platform x86 assembler with an Intel-like syntax
NASM (Netwide Assembler) is a widely used, open-source assembler for the x86 architecture that provides a flexible and portable way to write low-level machine code using an Intel-style syntax. It is designed to support a wide variety of output formats, making it suitable for different operating systems and development environments. NASM is known for its simplicity and clarity, allowing developers to write assembly code that is both readable and efficient. It is commonly used in system programming, operating system development, and performance-critical applications where direct hardware control is required. ... -
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. We actively develop Codon... -
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ko Easy Go Containers
Build and deploy Go applications on Kubernetes
...It's ideal for use cases where your image contains a single Go application without any/many dependencies on the OS base image (e.g., no cgo, no OS package dependencies). ko builds images by effectively executing go build on your local machine, and as such doesn't require docker to be installed. This can make it a good fit for lightweight CI/CD use cases. ko makes multi-platform builds easy, produces SBOMs by default, and includes support for simple YAML templating which makes it a powerful tool for Kubernetes applications. -
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Apache Flink
Stream processing framework with powerful stream
...Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. 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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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory... -
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MQTTnet
High performance .NET library for MQTT based communication
MQTTnet is a high-performance .NET library for MQTT-based communication. It provides an MQTT client and an MQTT server (broker) and supports the MQTT protocol up to version 5. TLS support for client and server (but not UWP servers). Extensible communication channels (e.g. In-Memory, TCP, TCP+TLS, WS). Lightweight (only the low-level implementation of MQTT, no overhead). Performance optimized (processing ~150.000 messages/second). Uniform API across all supported versions of the MQTT protocol. Tested on the local machine (Intel i7 8700K) with MQTTnet client and server running in the same process using the TCP channel. ... -
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electron-builder
A complete solution to package and build a Electron app
A complete solution to package and build a ready-for-distribution Electron, Proton Native app for macOS, Windows and Linux with “auto update” support out of the box. You can use electron-builder only to pack your electron app in a AppImage, Snaps, Debian package, NSIS, macOS installer component package (pkg) and other distributable formats. Build and publish in parallel, using hard links on CI server to reduce IO and disk space usage. Docker images to build Electron app for Linux or Windows... -
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PennyLane
A cross-platform Python library for differentiable programming
...Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. The same quantum circuit model can be run on different devices. Install plugins to run your computational circuits on more devices, including Strawberry Fields, Amazon Braket, Qiskit and IBM Q, Google Cirq, Rigetti Forest, and the Microsoft QDK. -
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Qiling
Qiling Advanced Binary Emulation Framework
Cross-platform and multi-arch ultra lightweight emulator. Supported OS: Linux, MacOS, Windows, FreeBSD, DOS and UEFI. Support Arch: x86(16/32/64), ARM(64) MIPS, EVM and WASM. It also support Linux Kernel Module(.ko) , Windows Driver(.sys) and MacOS Kernel(.kext) via Demigod. Binary instrumentation and API are Qiling Framework's main focus and priority. It is designed for reverse engineers - thus there is no need to rebuild another sand boxing tool. Using Qiling Framework saves you time. ... -
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PyMC3
Probabilistic programming in Python
...PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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Gmail Cleaner
Web based GUI to cleanup gmail delete, mark as read
...The tool employs smart filtering options such as age, size, category, and sender, and runs entirely locally — meaning all Gmail API interactions happen on the user’s own machine without sending data to external servers. With Docker and native Python support, Gmail Cleaner works on Linux, macOS, and Windows and makes large-scale inbox management accessible to both casual and power users. It includes features like progress tracking, smart filters, label management, and CSV export for metadata, making it versatile for different cleanup strategies. -
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Daytona
The Open Source Dev Environment Manager
Set up a development environment on any infrastructure, with a single command. -
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Functions Framework for Node.js
FaaS (Function as a service) framework for writing portable Node.js
Functions Framework for Node.js is a lightweight runtime library that allows developers to write and run portable serverless functions locally or in cloud environments using standard Node.js. It provides a consistent execution model that mimics Google Cloud Functions, enabling developers to build, test, and debug functions on their local machine before deploying them to production. The framework supports multiple function signature types, including HTTP-based functions and event-driven functions, and automatically parses incoming request payloads into structured objects that can be easily consumed by application logic. It also includes support for CloudEvents, allowing seamless integration with event-driven architectures and modern cloud-native systems. ... -
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Brownie
A Python-based development and testing framework for smart contracts
Brownie is a Python-based development and testing framework for smart contracts targeting the Ethereum Virtual Machine. Powerful debugging tools, including python-style tracebacks and custom error strings. The recommended way to install Brownie is via pipx. pipx installs Brownie into a virtual environment and makes it available directly from the command-line. Once installed, you will never have to activate a virtual environment prior to using Brownie. Brownie documentation is hosted at Read...
