mlops-platformsCompare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Stars: ✭ 293 (+187.25%)
hi-mlHI-ML toolbox for deep learning for medical imaging and Azure integration
Stars: ✭ 150 (+47.06%)
az-ml-realtime-scoreArchitecture for deploying real-time scoring of machine learning models using Azure Machine Learning
Stars: ✭ 40 (-60.78%)
aml-computeGitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.
Stars: ✭ 19 (-81.37%)
k3aiA lightweight tool to get an AI Infrastructure Stack up in minutes not days. K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.
Stars: ✭ 105 (+2.94%)
ck-mlopsA collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:
Stars: ✭ 15 (-85.29%)
monai-deployMONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.
Stars: ✭ 56 (-45.1%)
aml-deployGitHub Action that allows you to deploy machine learning models in Azure Machine Learning.
Stars: ✭ 37 (-63.73%)
aml-registermodelGitHub Action that allows you to register models to your Azure Machine Learning Workspace.
Stars: ✭ 14 (-86.27%)
cartpole-rl-remoteCartPole game by Reinforcement Learning, a journey from training to inference
Stars: ✭ 24 (-76.47%)
actions-ml-cicdA Collection of GitHub Actions That Facilitate MLOps
Stars: ✭ 181 (+77.45%)
recommendations-for-engineersAll of my recommendations for aspiring engineers in a single place, coming from various areas of interest.
Stars: ✭ 81 (-20.59%)
Python-MLOps-CookbookThis is an example of a Containerized Flask Application that can deploy to many target environments including: AWS, GCP and Azure.
Stars: ✭ 269 (+163.73%)
ml-workflow-automationPython Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.
Stars: ✭ 44 (-56.86%)
damaa simplified machine learning container platform that helps teams get started with an automated workflow
Stars: ✭ 76 (-25.49%)
fusemlFuseML aims to provide an MLOps framework as the medium dynamically integrating together the AI/ML tools of your choice. It's an extensible tool built through collaboration, where Data Engineers and DevOps Engineers can come together and contribute with reusable integration code.
Stars: ✭ 73 (-28.43%)
MLOps-Specialization-NotesNotes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
Stars: ✭ 143 (+40.2%)
VickyBytesSubscribe to this GitHub repo to access the latest tech talks, tech demos, learning materials & modules, and developer community updates!
Stars: ✭ 48 (-52.94%)
krakenKraken CI is a continuous integration and testing system.
Stars: ✭ 87 (-14.71%)
mloperatorMachine Learning Operator & Controller for Kubernetes
Stars: ✭ 85 (-16.67%)
popmonMonitor the stability of a Pandas or Spark dataframe ⚙︎
Stars: ✭ 434 (+325.49%)
benderoptBlack-box optimization library
Stars: ✭ 84 (-17.65%)
mlops.toys🎲 A curated list of MLOps projects, tools and resources
Stars: ✭ 169 (+65.69%)
neptune-client📒 Experiment tracking tool and model registry
Stars: ✭ 348 (+241.18%)
cliPolyaxon Core Client & CLI to streamline MLOps
Stars: ✭ 18 (-82.35%)
oomstoreLightweight and Fast Feature Store Powered by Go (and Rust).
Stars: ✭ 76 (-25.49%)
great expectations actionA GitHub Action that makes it easy to use Great Expectations to validate your data pipelines in your CI workflows.
Stars: ✭ 66 (-35.29%)
fastapi-templateCompletely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.
Stars: ✭ 156 (+52.94%)
mrmrmRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
Stars: ✭ 170 (+66.67%)
e2eml-cookiecutterA generic template for building end-to-end machine learning projects
Stars: ✭ 26 (-74.51%)
chitraA multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
Stars: ✭ 210 (+105.88%)
krshA declarative KubeFlow Management Tool
Stars: ✭ 127 (+24.51%)
qaboardAlgorithm engineering is hard enough: don't spend your time with logistics. QA-Board organizes your runs and lets you visualize, compare and share results.
Stars: ✭ 48 (-52.94%)
MLOpsA project-based course on the foundations of MLOps with a focus on intuition and application.
Stars: ✭ 1,203 (+1079.41%)
mlops-workload-orchestratorThe MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.
Stars: ✭ 114 (+11.76%)
mltraceCoarse-grained lineage and tracing for machine learning pipelines.
Stars: ✭ 449 (+340.2%)
deepchecksTest Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
Stars: ✭ 1,595 (+1463.73%)
vertex-edgeA tool for training models to Vertex on Google Cloud Platform.
Stars: ✭ 24 (-76.47%)
hubPublic reusable components for Polyaxon
Stars: ✭ 8 (-92.16%)
awesome-open-mlopsThe Fuzzy Labs guide to the universe of open source MLOps
Stars: ✭ 304 (+198.04%)
domino-researchProjects developed by Domino's R&D team
Stars: ✭ 74 (-27.45%)
lightning-hydra-templatePyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡
Stars: ✭ 1,905 (+1767.65%)
kedro-airflow-k8sKedro Plugin to support running pipelines on Kubernetes using Airflow.
Stars: ✭ 22 (-78.43%)
tracemlEngine for ML/Data tracking, visualization, dashboards, and model UI for Polyaxon.
Stars: ✭ 445 (+336.27%)
metaflowbotSlack bot for monitoring your Metaflow flows!
Stars: ✭ 22 (-78.43%)
chartsHelm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.
Stars: ✭ 32 (-68.63%)
ml in productionA set of demo of deploying a Machine Learning Model in production using various methods
Stars: ✭ 49 (-51.96%)
MachinelearningnotebooksPython notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Stars: ✭ 2,790 (+2635.29%)
mlreefThe collaboration workspace for Machine Learning
Stars: ✭ 1,409 (+1281.37%)
datatileA library for managing, validating, summarizing, and visualizing data.
Stars: ✭ 419 (+310.78%)
ml-from-scratchAll content related to machine learning from my blog
Stars: ✭ 110 (+7.84%)
craneCrane is a easy-to-use and beautiful desktop application helps you build manage your container images.
Stars: ✭ 223 (+118.63%)
FakeFinderFakeFinder builds a modular framework for evaluating various deepfake detection models, offering a web application as well as API access for integration into existing workflows.
Stars: ✭ 29 (-71.57%)
ckPortable automation meta-framework to manage, describe, connect and reuse any artifacts, scripts, tools and workflows on any platform with any software and hardware in a non-intrusive way and with minimal effort. Try it using this tutorial to modularize and automate ML Systems benchmarking from the Student Cluster Competition at SC'22:
Stars: ✭ 501 (+391.18%)