awesome-kubernetes/v2-docs/mlops.md

# Machine Learning Ops (MLOps) and Data Science

!!! info "Architectural Context"
    Detailed reference for Machine Learning Ops (MLOps) and Data Science in the context of AI.

## Standard Reference

  - [Kubeflow](https://www.kubeflow.org)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [github: A very Long never ending Learning around Data Engineering & Machine' Learning](https://github.com/abhishek-ch/around-dataengineering)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [cd.foundation: Announcing the CD Foundation MLOps SIG](https://cd.foundation/blog/2020/02/11/announcing-the-cd-foundation-mlops-sig)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [dafriedman97.github.io: Machine Learning from Scratch](https://dafriedman97.github.io/mlbook/content/introduction.html)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [cortex.dev: How to build a pipeline to retrain and deploy models](https://www.cortex.dev/post/how-to-build-a-pipeline-to-retrain-and-deploy-models)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: A Kubernetes architecture for machine learning web-application' deployments](https://towardsdatascience.com/a-kubernetes-architecture-for-machine-learning-web-application-deployments-632f7765ef29)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [cloud.google.com: How to use a machine learning model from a Google Sheet' using BigQuery ML](https://cloud.google.com/blog/topics/developers-practitioners/how-use-machine-learning-model-google-sheet-using-bigquery-ml)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [itnext.io: Building ML Componentes on Kubernetes](https://itnext.io/building-ml-componentes-on-kubernetes-fc7e24cb9269)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Deploying An ML Model With FastAPI — A Succinct' Guide](https://towardsdatascience.com/deploying-an-ml-model-with-fastapi-a-succinct-guide-69eceda27b21)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [ML Platform Workshop](https://github.com/aporia-ai/mlplatform-workshop) <span class='md-tag md-tag--info'>⭐ 445</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Automatically Generate Machine Learning Code with' Just a Few Clicks](https://towardsdatascience.com/automatically-generate-machine-learning-code-with-just-a-few-clicks-7901b2334f97)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Schemafull streaming data processing in ML pipelines](https://towardsdatascience.com/using-kafka-with-avro-in-python-da85b3e0f966)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [analyticsindiamag.com: Top tools for enabling CI/CD in ML pipelines](https://analyticsindiamag.com/top-tools-for-enabling-ci-cd-in-ml-pipelines)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Step-by-step Approach to Build Your Machine Learning' API Using Fast API](https://towardsdatascience.com/step-by-step-approach-to-build-your-machine-learning-api-using-fast-api-21bd32f2bbdb)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [ravirajag.dev: MLOps Basics - Week 10: Summary](https://www.ravirajag.dev/blog/mlops-summary)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/workday-engineering: Implementing a Fully Automated Sharding' Strategy on Kubernetes for Multi-tenanted Machine Learning Applications](https://medium.com/workday-engineering/implementing-a-fully-automated-sharding-strategy-on-kubernetes-for-multi-tenanted-machine-learning-4371c48122ae)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/globant: Advantages of Deploying Machine Learning models with' Kubernetes 🌟](https://medium.com/globant/advantages-of-deploying-machine-learning-models-with-kubernetes-8454cc7c565e)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/pythoneers: MLOps: Tool Stack Requirement in Machine Learning' Pipeline](https://medium.com/pythoneers/mlops-tool-stack-requirement-in-machine-learning-pipeline-474b39f09dfc)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/formaloo: How no-code platforms are democratizing data science' and software development 🌟](https://medium.com/formaloo/making-databases-as-easy-as-playing-with-legos-no-code-no-problem-ed41d4fde269)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: From Jupyter Notebooks to Real-life: MLOps 🌟](https://towardsdatascience.com/from-jupyter-notebooks-to-real-life-mlops-9f590a7b5faa)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [datarevenue.com: Airflow vs. Luigi vs. Argo vs. MLFlow vs. KubeFlow](https://www.datarevenue.com/en-blog/airflow-vs-luigi-vs-argo-vs-mlflow-vs-kubeflow)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: From Dev to Deployment: An End to End Sentiment' Classifier App with MLflow, SageMaker, and Streamlit](https://towardsdatascience.com/from-dev-to-deployment-an-end-to-end-sentiment-classifier-app-with-mlflow-sagemaker-and-119043ea4203)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [elconfidencial.com: La batalla entre Google y Meta que nadie esperaba: revolucionar' la biología 🌟](https://www.elconfidencial.com/tecnologia/ciencia/2022-11-18/carrera-google-meta-revolucionar-biologia_3520865)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [swirlai.substack.com: SAI #08: Request-Response Model Deployment - The MLOps' Way, Spark - Executor Memory Structure and more... 🌟](https://swirlai.substack.com/p/sai-08-request-response-model-deployment)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [youtube: Making Friends with Machine Learning | Cassie Kozyrkov | playlist' 🌟](https://www.youtube.com/playlist?list=PLRKtJ4IpxJpDxl0NTvNYQWKCYzHNuy2xG)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [openai.com: Scaling Kubernetes to 7,500 nodes 🌟](https://openai.com/research/scaling-kubernetes-to-7500-nodes)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [huyenchip.com: Building LLM applications for production](https://huyenchip.com/2023/04/11/llm-engineering.html)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@study.uttam: Main Challenges of Machine Learning](https://medium.com/@study.uttam/main-challenges-of-machine-learning-eb06dffac3da)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [learn.microsoft.com: Machine Learning operations maturity model 🌟](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/mlops-maturity-model)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/ai-hero: Streamlining Machine Learning Operations (MLOps) with' Kubernetes and Terraform](https://medium.com/ai-hero/streamlining-machine-learning-operations-with-kubernetes-and-terraform-41baad37998e)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@karanshingde: Machine Learning in Production— Your Comprehensive' 101 Practical Guide](https://medium.com/@karanshingde/machine-learning-in-production-your-comprehensive-101-practical-guide-c7de0b5ad011)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: CI/CD for MLOps on GitLab (part 1)](https://marvelousmlops.substack.com/p/cicd-for-mlops-on-gitlab-part-1)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/aiguys: MLOps: Serving AI apps to million users](https://medium.com/aiguys/mlops-serving-ai-to-million-users-c77ed718b7ed)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: How to sell MLOps in large Organizations](https://marvelousmlops.substack.com/p/how-to-sell-mlops-in-large-organizations)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: MLOps roadmap 2024](https://marvelousmlops.substack.com/p/mlops-roadmap-2024)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Deploying LLM Apps to AWS, the Open-Source Self-Service' Way](https://towardsdatascience.com/deploying-llm-apps-to-aws-the-open-source-self-service-way-c54b8667d829)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [axelmendoza.com: The Ultimate Guide To ML Model Deployment In 2024](https://www.axelmendoza.com/posts/ml-model-deployment)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: Build Machine Learning Pipelines with Airflow and' Mlflow: Reservation Cancellation Forecasting](https://towardsdatascience.com/build-machine-learning-pipelines-with-airflow-and-mlflow-reservation-cancellation-forecasting-da675d409842)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: Technical roles in Data Science: Who is doing' what?](https://marvelousmlops.substack.com/p/technical-roles-in-data-science-who)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: Traceability & Reproducibility](https://marvelousmlops.substack.com/p/traceability-and-reproducibility)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: Learn Machine Learning and Neural Networks' without Frameworks](https://www.freecodecamp.org/news/learn-machine-learning-and-neural-networks-without-frameworks)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [seattledataguy.substack.com: Data Engineering Vs Machine Learning Pipelines](https://seattledataguy.substack.com/p/data-engineering-vs-machine-learning)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [aiml.com: Large Language Models Quiz (Medium)](https://aiml.com/quizzes/deep-learning-large-language-models-quiz-medium)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@samiullah6799: Different Roles in MLOps](https://medium.com/@samiullah6799/different-roles-in-mlops-0918de5321a4)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [dev.to/pavanbelagatti: Deploy Any AI/ML Application On Kubernetes: A Step-by-Step' Guide!](https://dev.to/pavanbelagatti/deploy-any-aiml-application-on-kubernetes-a-step-by-step-guide-2i37)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: Sharpen your cookiecutter: speed up repo creation' with workflows](https://marvelousmlops.substack.com/p/sharpen-your-cookiecutter-speed-up)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [decodingml.substack.com: How to ensure your models are fail-safe in production?](https://decodingml.substack.com/p/how-to-ensure-your-models-are-fail)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [freecodecamp.org: MLOps Course – Learn to Build Machine Learning Production' Grade Projects](https://www.freecodecamp.org/news/mlops-course-learn-to-build-machine-learning-production-grade-projects)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@kevin30101999: Machine Learning Pipeline using Argo workflow' 🌟](https://medium.com/@kevin30101999/machine-learning-pipeline-using-argo-workflow-be91feb07c41)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [roadmap.sh: MLOps roadmap](https://roadmap.sh/r?id=65a112f2b8633950ffcf38b6)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [Marvelous MLOps Substack](https://marvelousmlops.substack.com)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [decodingml.substack.com: Decoding ML Newsletter](https://decodingml.substack.com)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [youtube.com: Optimizing LLM Training with Airbnb's Next-Gen ML Platform](https://www.youtube.com/watch?v=-sZvzW40NrM&ab_channel=Anyscale)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [Ray](https://docs.ray.io/en/latest)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/mlearning-ai: The Best Object Detection Libraries That I Work' With](https://medium.com/mlearning-ai/the-best-object-detection-libraries-that-i-work-with-835428a1e01e)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [artifacthub.io: mlflow-server](https://artifacthub.io/packages/helm/mlflowserver/mlflow-server)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [pypi.org/project/airflow-provider-mlflow](https://pypi.org/project/airflow-provider-mlflow)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [infracloud.io: Machine Learning Orchestration on Kubernetes using Kubeflow](https://www.infracloud.io/blogs/machine-learning-orchestration-kubernetes-kubeflow)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [blog.devgenius.io: Kubeflow Cloud Deployment (AWS)](https://blog.devgenius.io/kubeflow-cloud-deployment-aws-46f739ccbb32)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [joseprsm.medium.com: How to build Machine Learning models that train themselves](https://joseprsm.medium.com/how-to-build-machine-learning-models-that-train-themselves-bbc87499ca5)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/dkatalis: Creating a Mutating Webhook for Great Good! Or: how' to automatically provision Pods on a specific node pool](https://medium.com/dkatalis/creating-a-mutating-webhook-for-great-good-b21acb941207)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [Union Cloud](https://www.union.ai)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [Machine Learning in Production. What does an end-to-end ML workflow look like in production? (transcript) 🌟🌟🌟](https://www.union.ai/blog-post/machine-learning-in-production)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [stackoverflow.com: How is Flyte tailored to "Data and Machine Learning"?](https://stackoverflow.com/questions/72657318/how-is-flyte-tailored-to-data-and-machine-learning)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [union.ai: Production-Grade ML Pipelines: Flyte™ vs. Kubeflow](https://www.union.ai/blog-post/production-grade-ml-pipelines-flyte-vs-kubeflow)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@timleonardDS: Who Let the DAGs out? Register an External DAG' with Flyte (Chapter 3)](https://medium.com/@timleonardDS/who-lets-the-dags-out-register-an-external-dag-with-flyte-chapter-3-bad0ea781119)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [aws.amazon.com: MLOps foundation roadmap for enterprises with Amazon SageMaker](https://aws.amazon.com/blogs/machine-learning/mlops-foundation-roadmap-for-enterprises-with-amazon-sagemaker)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [aws.amazon.com: Promote pipelines in a multi-environment setup using Amazon' SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD](https://aws.amazon.com/blogs/machine-learning/promote-pipelines-in-a-multi-environment-setup-using-amazon-sagemaker-model-registry-hashicorp-terraform-github-and-jenkins-ci-cd)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [bea.stollnitz.com: Creating batch endpoints in Azure ML](https://bea.stollnitz.com/blog/aml-batch-endpoint)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [blog.devops.dev: Mastering Machine Learning at Scale with Azure Machine' Learning](https://blog.devops.dev/mastering-machine-learning-at-scale-with-azure-machine-learning-dfaa4bf4353c)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [youtube: Deploy Convolutional Neural Network (CNN) on Azure with Python' | Deep Learning Deployment | MLOPS](https://www.youtube.com/watch?v=6sqGxVI3X1w)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [learn.microsoft.com: Azure Well-Architected Framework perspective on Azure' Machine Learning](https://learn.microsoft.com/en-us/azure/well-architected/service-guides/azure-machine-learning)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [marvelousmlops.substack.com: Model serving architectures on Databricks](https://marvelousmlops.substack.com/p/model-serving-architectures-on-databricks)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/sync-computing: Top 9 Lessons Learned about Databricks Jobs Serverless](https://medium.com/sync-computing/top-9-lessons-learned-about-databricks-jobs-serverless-41a43e99ded5)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [thenewstack.io: KServe: A Robust and Extensible Cloud Native Model Server](https://thenewstack.io/kserve-a-robust-and-extensible-cloud-native-model-server)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/bakdata: Scalable Machine Learning with Kafka Streams and KServe](https://medium.com/bakdata/scalable-machine-learning-with-kafka-streams-and-kserve-85308858d867)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [analyticsvidhya.com: Bring DevOps To Data Science With MLOps](https://www.analyticsvidhya.com/blog/2021/04/bring-devops-to-data-science-with-continuous-mlops)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [analyticsindiamag.com: Is coding necessary to work as a data scientist?](https://analyticsindiamag.com/is-coding-necessary-to-work-as-a-data-scientist)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [redhat.com: Introducing Red Hat OpenShift Data Science](https://www.redhat.com/en/blog/introducing-red-hat-openshift-data-science)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [towardsdatascience.com: From DevOps to MLOPS: Integrate Machine Learning' Models using Jenkins and Docker](https://towardsdatascience.com/from-devops-to-mlops-integrate-machine-learning-models-using-jenkins-and-docker-79034dbedf1)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [catalog.ngc.nvidia.com: NVIDIA GPU Operator - Helm chart 🌟🌟🌟](https://catalog.ngc.nvidia.com/orgs/nvidia/helm-charts/gpu-operator)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [jimangel.io: A Practical Guide to Running NVIDIA GPUs on Kubernetes](https://www.jimangel.io/posts/nvidia-rtx-gpu-kubernetes-setup)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [huggingface.co: Implementing Fractional GPUs in Kubernetes with Aliyun Scheduler](https://huggingface.co/blog/NileshInfer/implementing-fractional-gpus-in-kubernetes)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [medium.com/@bchenjh: Distributed full fine-tuning of Llama2 on Kubernetes](https://medium.com/@bchenjh/full-fine-tuning-of-llama2-on-kubernetes-a983e1eb2259)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [bodywork-ml/bodywork-core: Bodywork](https://github.com/bodywork-ml/bodywork-core) <span class='md-tag md-tag--info'>⭐ 436</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [learn.iterative.ai: Iterative Tools for Data Scientists & Analysts](https://learn.iterative.ai)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [DVC](https://marketplace.visualstudio.com/items?itemName=Iterative.dvc)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [tensorchord/envd: Reproducible development environment for AI/ML 🌟](https://github.com/tensorchord/envd) <span class='md-tag md-tag--info'>⭐ 2206</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [postgresml/postgresml 🌟](https://github.com/postgresml/postgresml) <span class='md-tag md-tag--info'>⭐ 6791</span>  <span class='md-tag md-tag--info'>[ENTERPRISE-STABLE]</span>
  - [blog.devgenius.io: Training model with Jenkins using docker: MLOPS](https://blog.devgenius.io/training-model-with-jenkins-using-docker-mlops-b18579ddb677)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [vaex.io](https://vaex.io)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [thenewstack.io: 7 Must-Have Python Tools for ML Devs and Data Scientists' 🌟](https://thenewstack.io/7-must-have-python-tools-for-ml-devs-and-data-scientists)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [github.com/SymbioticLab/Oobleck: Oobleck - Resilient Distributed Training' Framework](https://github.com/SymbioticLab/Oobleck) <span class='md-tag md-tag--info'>⭐ 100</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [github.com/aimhubio/aim](https://github.com/aimhubio/aim) <span class='md-tag md-tag--info'>⭐ 6126</span>  <span class='md-tag md-tag--info'>[ENTERPRISE-STABLE]</span>
  - [github.com/XuehaiPan/nvitop 🌟](https://github.com/XuehaiPan/nvitop) <span class='md-tag md-tag--info'>⭐ 6921</span>  <span class='md-tag md-tag--info'>[ENTERPRISE-STABLE]</span>
  - [github.com/Netflix/metaflow 🌟](https://github.com/Netflix/metaflow) <span class='md-tag md-tag--info'>⭐ 10107</span>  <span class='md-tag md-tag--info'>[ENTERPRISE-STABLE]</span>
  - [zenml.io: ZenML](https://www.zenml.io)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [betterprogramming.pub: Attach a Visual Debugger to ML-training Jobs on Kubernetes](https://betterprogramming.pub/attach-a-visual-debugger-to-ml-training-jobs-on-kubernetes-eb9678389f1f)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [fepegar/vesseg](https://github.com/fepegar/vesseg) <span class='md-tag md-tag--info'>⭐ 44</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [github.com/10tanmay100: MEDICAL-DATA-PROJECT-END2END-WITH-FEW-MLOPS](https://github.com/10tanmay100/MEDICAL-DATA-PROJECT-END2END-WITH-FEW-MLOPS) <span class='md-tag md-tag--info'>⭐ 3</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [dair-ai/ML-Course-Notes: ML Course Notes 🌟](https://github.com/dair-ai/ML-Course-Notes) <span class='md-tag md-tag--info'>⭐ 6455</span>  <span class='md-tag md-tag--info'>[ENTERPRISE-STABLE]</span>
  - [Kaggle Competitions](https://www.kaggle.com/competitions)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [kaggle.com: Sports Car Prices dataset](https://www.kaggle.com/datasets/rkiattisak/sports-car-prices-dataset)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [isic-archive.com](https://www.isic-archive.com/#!/topWithHeader/wideContentTop/main)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>
  - [freecodecamp.org: How to Download a Kaggle Dataset Directly to a Google' Colab Notebook](https://www.freecodecamp.org/news/how-to-download-kaggle-dataset-to-google-colab)  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span>

## Data Engineering

### CI-CD for ML

  - **(2022)** [semaphoreci.com: Why Do We Need DevOps for ML Data?](https://semaphore.io/blog/devops-ml-data) <span class='md-tag md-tag--warning'>[N/A CONTENT]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Connects classic CI/CD DevOps approaches to data-centric ML development (DataOps). Emphasizes raw data version control, schema drift verification, and deterministic pipeline stages to prevent silent model failures.
## Data Labeling

### Argilla

  - **(2026)** [==rubrix==](https://github.com/argilla-io/argilla) <span class='md-tag md-tag--info'>⭐ 4981</span> <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> 🌟🌟🌟🌟🌟 <span class='md-tag md-tag--success'>[DE FACTO STANDARD]</span> — Formerly Rubrix, Argilla is an open-source data curation platform designed for AI and LLM workflows. Enables continuous human-in-the-loop (HITL) fine-tuning cycles. Integrates seamlessly with Hugging Face and SpaCy pipelines.
## Data Science and ML

### Computer Vision

#### Segment Anything

  - **(2023)** [==github.com/CASIA-IVA-Lab/FastSAM==](https://github.com/CASIA-LMC-Lab/FastSAM) <span class='md-tag md-tag--info'>⭐ 8342</span> <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> 🌟🌟🌟🌟🌟 <span class='md-tag md-tag--success'>[DE FACTO STANDARD]</span> — Fast Segment Anything Model (FastSAM) is a highly efficient, CNN-based real-time alternative to the original SAM. It achieves comparable zero-shot instance segmentation quality at a significantly lower computational footprint, making it ideal for edge computing and low-latency production pipelines.
### Document AI

#### OCR and Layout Analysis

  - **(2024)** [==github.com/VikParuchuri/surya==](https://github.com/datalab-to/surya) <span class='md-tag md-tag--info'>⭐ 19766</span> <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> 🌟🌟🌟🌟🌟 <span class='md-tag md-tag--success'>[DE FACTO STANDARD]</span> <span class='md-tag md-tag--info'>[LEGACY]</span> — Surya provides robust, multi-lingual document OCR and highly accurate layout analysis. It leverages advanced deep learning architectures to process dense, complex documents (such as academic papers and financial statements) with structural precision, presenting a lighter alternative to legacy commercial engines.
### ML Systems Design

#### Real-Time RAG

  - **(2024)** [==github.com/decodingml: Real-time news search engine using Upstash Kafka and Vector DB==](https://github.com/decodingai-magazine/articles-code/tree/main/articles/ml_system_design/real_time_news_search_with_upstash_kafka_and_vector_db) <span class='md-tag md-tag--info'>⭐ 139</span> <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> 🌟🌟🌟🌟🌟 <span class='md-tag md-tag--success'>[DE FACTO STANDARD]</span> — A practical system architecture blueprint for building a real-time news search engine. Utilizing Upstash managed Kafka for streaming ingest and a Vector DB for semantic indexing, this reference demonstrates how to construct serverless, high-throughput event-driven retrieval-augmented generation (RAG) pipelines.
### MLOps

#### Model Versioning

  - **(2024)** [docs.microsoft.com: Machine Learning Experimentation in VS Code with DVC Extension](https://learn.microsoft.com/en-us/shows/vs-code-livestreams/machine-learning-experimentation-in-vs-code-with-dvc-extension) <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--primary'>[DOCUMENTATION]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — An official guide demonstrating the integration of Data Version Control (DVC) within VS Code to manage datasets, track experiments, and version models natively. This approach bridges software engineering standards with data science pipelines, ensuring reproducibility of complex ML assets directly from the developer's workspace.
## GPU Management

### Nix

  - **(2023)** [canvatechblog.com: Supporting GPU-accelerated Machine Learning with Kubernetes and Nix](https://www.canva.dev/blog/engineering/supporting-gpu-accelerated-machine-learning-with-kubernetes-and-nix) <span class='md-tag md-tag--warning'>[NIX CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — A high-density engineering breakdown on using Nix alongside Kubernetes to deploy GPU-bound workloads. Solves library drift in CUDA dependency networks, ensuring highly reproducible ML platform environments.
## Generative AI

### LLM Fine-tuning

#### Llama recipes

  - **(2026)** [==github.com/meta-llama/llama-recipes==](https://github.com/meta-llama/llama-cookbook) <span class='md-tag md-tag--info'>⭐ 18334</span> <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> 🌟🌟🌟🌟🌟 <span class='md-tag md-tag--success'>[DE FACTO STANDARD]</span> — Meta's primary cookbook for deploying and fine-tuning Llama models. Features scalable recipes for parameter-efficient tuning (PEFT, LoRA), Quantization, and deployment templates inside microservices frameworks.
## Infrastructure Abstraction

### Flyte

  - **(2022)** [mlops.community: MLOps Simplified: orchestrating ML pipelines with infrastructure abstraction. Enabled by Flyte](https://mlops.community/blog/flyte-mlops-simplified) <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Details how Flyte isolates platform operations from application execution. Machine learning engineers configure compute limits natively inside Python scripts, leaving cluster management to core operations.
## Infrastructure-As-Code

### Dependency Management

#### Nix Packages

  - **(2026)** [Nix](https://nix.dev/manual/nix/2.28) <span class='md-tag md-tag--warning'>[NIX CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span> <span class='md-tag md-tag--primary'>[DOCUMENTATION]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Reference manual for Nix package manager and dependency architectures. Discusses underlying system interactions, specifically comparing standard Docker host volumes with Nix's deterministic sandboxed build environments.
## Model Serving

### Microservices

  - **(2021)** [cloudblogs.microsoft.com: Simple steps to create scalable processes to deploy ML models as microservices](https://opensource.microsoft.com/blog/2021/07/09/simple-steps-to-create-scalable-processes-to-deploy-ml-models-as-microservices) <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — A strategic guide outlining the transformation of raw trained ML algorithms into lightweight, scalable containerised microservices. Highlights REST and gRPC wrapper packaging models, optimizing response payloads for low-latency scoring endpoints.
## Model Tracking

### Azure Integration

  - **(2024)** [docs.microsoft.com: MLflow and Azure Machine Learning](https://learn.microsoft.com/en-us/azure/machine-learning/concept-mlflow?view=azureml-api-2) <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--primary'>[DOCUMENTATION]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Deep technical reference on integrating MLflow telemetry inside Microsoft Azure's cloud infrastructure. Standardizes metrics tracking, hyperparameter recording, and artifact storage across hybrid deployments.
## Open Source AI

### Industry Analysis

  - **(2022)** [infoworld.com: 13 open source projects transforming AI and machine learning](https://www.infoworld.com/article/2336757/16-open-source-projects-transforming-ai-and-machine-learning.html) <span class='md-tag md-tag--warning'>[N/A CONTENT]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Compiles core open-source projects revolutionizing machine learning architectures. Explores shifts in data orchestration, distributed training pipelines, and deployment runtimes that lower enterprise adoption barriers.
## Orchestration

### Flyte (1)

  - **(2022)** [mlops.community: MLOps with Flyte: The Convergence of Workflows Between Machine Learning and Engineering](https://mlops.community/blog/mlops-with-flyte-the-convergence-of-workflows-between-machine-learning-and-engineering) <span class='md-tag md-tag--warning'>[PYTHON CONTENT]</span> <span class='md-tag md-tag--critical'>[ADVANCED LEVEL]</span>  <span class='md-tag md-tag--info'>[COMMUNITY-TOOL]</span> — Highlights Flyte as a robust, Kubernetes-native pipeline engine designed to unify scientific model exploration with enterprise deployment workflows. Explores its strongly-typed architecture to manage data flow.

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