Topic: mlops Goto Github
Some thing interesting about mlops
Some thing interesting about mlops
mlops,Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
Organization: activeloopai
Home Page: https://activeloop.ai
mlops,Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Organization: aimhubio
Home Page: https://aimstack.io
mlops,ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Organization: allegroai
Home Page: https://clear.ml/docs
mlops,Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Organization: apache
Home Page: https://airflow.apache.org/
mlops,Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
Organization: argilla-io
Home Page: https://docs.argilla.io
mlops,Workflow Engine for Kubernetes
Organization: argoproj
Home Page: https://argo-workflows.readthedocs.io/
mlops,AI Observability & Evaluation
Organization: arize-ai
Home Page: https://docs.arize.com/phoenix
mlops,PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
User: ashleve
mlops,Turns Data and AI algorithms into production-ready web applications in no time.
Organization: avaiga
Home Page: https://www.taipy.io
mlops,Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Organization: aws
Home Page: https://sagemaker-examples.readthedocs.io
mlops,The easiest way to serve AI apps and models - Build reliable Inference APIs, LLM apps, Multi-model chains, RAG service, and much more!
Organization: bentoml
Home Page: https://bentoml.com
mlops,Run any open-source LLMs, such as Llama 3.1, Gemma, as OpenAI compatible API endpoint in the cloud.
Organization: bentoml
Home Page: https://bentoml.com
mlops,A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
User: chiphuyen
Home Page: https://huyenchip.com/machine-learning-systems-design/toc.html
mlops,An orchestration platform for the development, production, and observation of data assets.
Organization: dagster-io
Home Page: https://dagster.io
mlops,Free MLOps course from DataTalks.Club
Organization: datatalksclub
mlops,Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
Organization: deepchecks
Home Page: https://docs.deepchecks.com/stable
mlops,A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Organization: ethicalml
Home Page: https://ethicalml.github.io/awesome-production-machine-learning
mlops,Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Organization: evidentlyai
Home Page: https://www.evidentlyai.com/evidently-oss
mlops,The Open Source Feature Store for Machine Learning
Organization: feast-dev
Home Page: https://feast.dev
mlops,FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
Organization: fedml-ai
Home Page: https://TensorOpera.ai
mlops,Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Organization: flyteorg
Home Page: https://flyte.org
mlops,🐢 Open-Source Evaluation & Testing for LLMs and ML models
Organization: giskard-ai
Home Page: https://docs.giskard.ai
mlops,Learn how to design, develop, deploy and iterate on production-grade ML applications.
User: gokumohandas
Home Page: https://madewithml.com
mlops,Always know what to expect from your data.
Organization: great-expectations
Home Page: https://docs.greatexpectations.io/
mlops,A collection of scientific methods, processes, algorithms, and systems to build stories & models.
User: hemansnation
Home Page: https://www.himanshuramchandani.co/
mlops,Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
Organization: higgsfield-ai
mlops,Label Studio is a multi-type data labeling and annotation tool with standardized output format
Organization: humansignal
Home Page: https://labelstud.io
mlops,☁️ Build multimodal AI applications with cloud-native stack
Organization: jina-ai
Home Page: https://docs.jina.ai
mlops,Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Organization: kedro-org
Home Page: https://kedro.org
mlops,:sunglasses: A curated list of awesome MLOps tools
User: kelvins
mlops,Standardized Serverless ML Inference Platform on Kubernetes
Organization: kserve
Home Page: https://kserve.github.io/website/
mlops,Machine Learning Pipelines for Kubeflow
Organization: kubeflow
Home Page: https://www.kubeflow.org/docs/components/pipelines/
mlops,Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
Organization: lancedb
Home Page: https://lancedb.github.io/lance/
mlops,An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Organization: microsoft
Home Page: https://nni.readthedocs.io
mlops,:rocket: Build and manage real-life ML, AI, and data science projects with ease!
Organization: netflix
Home Page: https://metaflow.org
mlops,The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Organization: ploomber
Home Page: https://docs.ploomber.io
mlops,MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Organization: polyaxon
Home Page: https://polyaxon.com
mlops,Serve, optimize and scale PyTorch models in production
Organization: pytorch
Home Page: https://pytorch.org/serve/
mlops,Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Organization: qdrant
Home Page: https://qdrant.tech
mlops,An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Organization: seldonio
Home Page: https://www.seldon.io/tech/products/core/
mlops,This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
User: skalskip
mlops,Machine Learning Engineering Open Book
User: stas00
Home Page: https://stasosphere.com/machine-learning/
mlops,Superduper: Bring AI to your database! Integrate AI models and workflows with your database to implement custom AI applications, without moving your data. Including streaming inference, scalable model hosting, training and vector search.
Organization: superduper-io
Home Page: https://superduper.io
mlops,cube studio开源云原生一站式机器学习/深度学习/大模型AI平台,支持sso登录,多租户,大数据平台对接,notebook在线开发,拖拉拽任务流pipeline编排,多机多卡分布式训练,超参搜索,推理服务VGPU,边缘计算,serverless,标注平台,自动化标注,数据集管理,大模型微调,vllm大模型推理,llmops,私有知识库,AI模型应用商店,支持模型一键开发/推理/微调,支持国产cpu/gpu/npu芯片,支持RDMA,支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/spark/ray/volcano分布式
Organization: tencentmusic
mlops,An awesome & curated list of best LLMOps tools for developers
Organization: tensorchord
mlops,A curated list of references for MLOps
User: visenger
Home Page: https://ml-ops.org
mlops,A high-throughput and memory-efficient inference and serving engine for LLMs
Organization: vllm-project
Home Page: https://docs.vllm.ai
mlops,🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Organization: wandb
Home Page: https://wandb.ai
mlops,Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Organization: weaviate
Home Page: https://weaviate.io/developers/weaviate/
mlops,ZenML 🙏: The bridge between ML and Ops. https://zenml.io.
Organization: zenml-io
Home Page: https://zenml.io
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🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.