Search Results for "open source project" - Page 15
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Showing 1153 open source projects for "open source project"
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Enterprise-grade ITSM, for every businessFreshservice 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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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can... -
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elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank
The Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob. -
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The Operator Splitting QP Solver
The Operator Splitting QP Solver
OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust. -
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Advanced Solutions Lab
This repos contains notebooks for the Advanced Solutions Lab
This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level. -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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KerasTuner
A Hyperparameter Tuning Library for Keras
KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search... -
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pycm
Multi-class confusion matrix library in Python
PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers. -
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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. ... -
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Jina-Serve
Build multimodal AI applications with cloud-native stack
Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as Kubernetes. ... -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training models, creating predictions, evaluating models, and bundling the model files and configuration for easy deployment. ... -
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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... -
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DeepPavlov
A library for deep learning end-to-end dialog systems and chatbots
...Guides explain the concepts and components of DeepPavlov. Follow step-by-step instructions to install, configure and extend DeepPavlov framework for your use case. DeepPavlov is an open-source framework for chatbots and virtual assistants development. It has comprehensive and flexible tools that let developers and NLP researchers create production-ready conversational skills and complex multi-skill conversational assistants. Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. ... -
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AutoMLOps
Build MLOps Pipelines in Minutes
AutoMLOps is a service that generates, provisions, and deploys CI/CD integrated MLOps pipelines, bridging the gap between Data Science and DevOps. AutoMLOps provides a repeatable process that dramatically reduces the time required to build MLOps pipelines. The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives... -
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Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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SkyPilot
SkyPilot: Run AI and batch jobs on any infra
SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface. -
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omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. ... -
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Advanced NLP with spaCy
Advanced NLP with spaCy: A free online course
Advanced NLP with spaCy is an open-source educational repository that provides the materials for an interactive course on advanced natural language processing using the spaCy library. The course is designed to teach developers how to build real-world NLP systems by combining rule-based techniques with machine learning models. The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and training custom NLP models. ... -
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HeavyDB
HeavyDB (formerly MapD/OmniSciDB)
HeavyDB is an open-source GPU-accelerated analytical database designed to perform extremely fast queries on large datasets. The system is built as a SQL-based relational columnar database engine that leverages modern hardware parallelism, including GPUs and multicore CPUs. Its architecture allows users to query datasets containing billions of rows in milliseconds without requiring traditional indexing, pre-aggregation, or sampling techniques. -
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Ploomber
The fastest way to build data pipelines
Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. ... -
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MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. -
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Adversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) - Python Library for ML security
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,... -
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Intel Extension for PyTorch
A Python package for extending the official PyTorch
Intel® Extension for PyTorch* extends PyTorch* with up-to-date features optimizations for an extra performance boost on Intel hardware. Optimizations take advantage of Intel® Advanced Vector Extensions 512 (Intel® AVX-512) Vector Neural Network Instructions (VNNI) and Intel® Advanced Matrix Extensions (Intel® AMX) on Intel CPUs as well as Intel Xe Matrix Extensions (XMX) AI engines on Intel discrete GPUs. Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel... -
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fastdup
An unsupervised and free tool for image and video dataset analysis
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. -
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Physical Symbolic Optimization (Φ-SO)
Physical Symbolic Optimization
Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. -
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Llama Recipes
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method
The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. The examples here showcase how to run...
