Topic: ml-ops Goto Github
Some thing interesting about ml-ops
Some thing interesting about ml-ops
ml-ops,These are my personal notes regarding Machine Learning DevOps stuff
User: a-ngo
ml-ops,A ready to use architecture for processing data and performing machine learning in Azure
User: adampaternostro
ml-ops,A simple Python example of a Model Service that can be fronted by the Model Sidecar
Organization: ameron-ai
ml-ops,This GitHub repository showcases the implementation of a comprehensive end-to-end MLOps pipeline using Amazon SageMaker pipelines to deploy and manage 100x machine learning models. The pipeline covers data pre-processing, model training/re-training, hyperparameter tuning, data quality check,model quality check, model registry, and model deployment.
Organization: aws-samples
ml-ops,Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.
Organization: azure-samples
ml-ops,A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Organization: ethicalml
Home Page: https://ethical.institute/principles.html
ml-ops,Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)
User: gagan-iitb
Home Page: https://github.com/gagan-iitb/ComputerSysDesign
ml-ops,Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
User: gasparian
ml-ops,Find the samples, in the test data, on which your (generative) model makes mistakes.
Organization: guidelabs
ml-ops,A list of interesting bookmarks, blogs, channels, papers, and anything that can be considered as a day to day reference for an AI, DS, ML, or DL practioner. [WIP]
User: haddagart
ml-ops,Data Science Experiments Repository of Ideas2IT
Organization: ideas2it
ml-ops,Sample Airflow ML Pipelines
User: jasmeetsb
ml-ops,Project that uses AWS SageMaker to train a neural network and serve the model
User: jefersonalves
ml-ops,A pipeline to CI/CD of a machine learning model on Google Cloud Run
User: jgvaraujo
ml-ops,Demo usage of Weights & Biases for ML Ops
User: kayvane1
ml-ops,Vehicle data classification (supervised, unsupervised learning)
User: lfunderburk
ml-ops,A Collection of GitHub Actions That Facilitate MLOps
Organization: machine-learning-apps
Home Page: https://youtu.be/Ll50l3fsoYs
ml-ops,Slides of my talk "Is Your ML Model Trustworthy?" at the MLOps World Conference on the 16th of June 2021.
User: mariagrandury
Home Page: https://is-your-ml-model-trustworthy.netlify.app/1
ml-ops,A prefect extension that builds on top of the task decorator to reduce negative engineering!
User: marwan116
ml-ops,The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt
User: matsmoll
Home Page: https://www.aligned.codes
ml-ops,Repository showcasing ML Ops practices with kubeflow and mlflow
User: mgthetrain
ml-ops,interactive coding environment for microservices demo
Organization: ml-starter-packs
ml-ops,This machine learning pipeline project aims to develop an ML model to identify bank customer churn.
User: nikofebrianur
ml-ops,This machine learning pipeline project aims to develop an ML model to identify customer sentiment from French-language tweets on social media.
User: nikofebrianur
ml-ops,Efficient streaming data ingestion, transformation & activation
Organization: nucleusengineering
ml-ops,Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines
Organization: prefecthq
Home Page: https://prefect.io
ml-ops,Raccogliamo qui tutti i link alle risorse menzionate durante i nostri QShare
Organization: quantyca
Home Page: https://quantyca.it/
ml-ops,ORBIT SMKN 4 Bandung team repository for Turnamen Sains Data Nasional 2022 coordinated by Cybertrend Data Academy and Asosiasi Data Sains dan AI Indonesia with supported by several government agencies and universities in Indonesia.
User: rafka-imandaputra
ml-ops,A curated list of articles that cover the software engineering best practices for building machine learning applications.
Organization: se-ml
ml-ops,An open-source ML pipeline development platform
Organization: sematic-ai
ml-ops,The universal data connector
Organization: spoke-data
Home Page: https://www.spoke.sh
ml-ops,A library of computer vision models and a streamlined framework for training them.
User: thenewflesh
ml-ops,Fire up your models with the flame 🔥
Organization: vortico
Home Page: https://flama.dev
ml-ops,Examples showcasing Flama 🔥
Organization: vortico
Home Page: https://flama.dev
ml-ops,Repo for running Whylogs as part of a CI workflow using github actions.
Organization: whylabs
Home Page: http://whylogs.readthedocs.io/
ml-ops,Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
User: ziss11
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Open source projects and samples from Microsoft.
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China tencent open source team.