{"id":42307870,"url":"https://github.com/paiml/practical-mlops-book","last_synced_at":"2026-02-21T01:32:49.076Z","repository":{"id":38738967,"uuid":"311069405","full_name":"paiml/practical-mlops-book","owner":"paiml","description":"[Book-2021] Practical MLOps O'Reilly Book","archived":false,"fork":false,"pushed_at":"2025-01-10T22:52:14.000Z","size":4530,"stargazers_count":729,"open_issues_count":2,"forks_count":292,"subscribers_count":19,"default_branch":"main","last_synced_at":"2025-01-10T23:28:06.955Z","etag":null,"topics":["cloud","learning","machine","machine-learning","oreilly-books","practical-mlops","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/paiml.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-11-08T13:30:47.000Z","updated_at":"2025-01-10T22:52:18.000Z","dependencies_parsed_at":"2025-01-10T23:25:18.117Z","dependency_job_id":"9f3eb97e-e89a-4dab-90b0-6a211724b001","html_url":"https://github.com/paiml/practical-mlops-book","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/paiml/practical-mlops-book","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paiml%2Fpractical-mlops-book","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paiml%2Fpractical-mlops-book/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paiml%2Fpractical-mlops-book/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paiml%2Fpractical-mlops-book/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/paiml","download_url":"https://codeload.github.com/paiml/practical-mlops-book/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paiml%2Fpractical-mlops-book/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29574065,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-18T08:38:15.585Z","status":"ssl_error","status_checked_at":"2026-02-18T08:38:14.917Z","response_time":162,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cloud","learning","machine","machine-learning","oreilly-books","practical-mlops","python"],"created_at":"2026-01-27T11:12:46.286Z","updated_at":"2026-02-21T01:32:49.062Z","avatar_url":"https://github.com/paiml.png","language":"Jupyter Notebook","readme":"## 🎓 Pragmatic AI Labs | Join 1M+ ML Engineers\n\n### 🔥 Hot Course Offers:\n* 🤖 [Coursera Hugging Face AI Development Specialization](https://www.coursera.org/specializations/hugging-face-ai-development) - Build Production AI systems with Hugging Face in Pure Rust\n* 🤖 [Master GenAI Engineering](https://ds500.paiml.com/learn/course/0bbb5/) - Build Production AI Systems\n* 🦀 [Learn Professional Rust](https://ds500.paiml.com/learn/course/g6u1k/) - Industry-Grade Development\n* 📊 [AWS AI \u0026 Analytics](https://ds500.paiml.com/learn/course/31si1/) - Scale Your ML in Cloud\n* ⚡ [Production GenAI on AWS](https://ds500.paiml.com/learn/course/ehks1/) - Deploy at Enterprise Scale\n* 🛠️ [Rust DevOps Mastery](https://ds500.paiml.com/learn/course/ex8eu/) - Automate Everything\n\n### 🚀 Level Up Your Career:\n* 💼 [Production ML Program](https://paiml.com) - Complete MLOps \u0026 Cloud Mastery\n* 🎯 [Start Learning Now](https://ds500.paiml.com) - Fast-Track Your ML Career\n* 🏢 Trusted by Fortune 500 Teams\n\nLearn end-to-end ML engineering from industry veterans at [PAIML.COM](https://paiml.com)\n## Practical MLOps, an O'Reilly Book\n\nThis is a public repo where code samples are stored for the book Practical MLOps.\n\n![mlops-color](https://user-images.githubusercontent.com/58792/121539559-c6787e80-c9d3-11eb-9f48-5d25924fad25.png)\n* [Read Practical MLOps Online](https://learning.oreilly.com/library/view/practical-mlops/9781098103002/)\n* [Purchase Practical MLOps](https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017)\n\n## Tentative Outline\n\n### Chapter 1: Introduction to MLOps\n#### Source Code Chapter 1:\n   * [Multi-cloud Github Actions Demo](https://github.com/noahgift/github-actions-demo)\n\n### Chapter 2: MLOps Foundations\n#### Source Code Chapter 2:\n\n   * https://github.com/noahgift/cloud-bash-essentials\n   * https://github.com/noahgift/regression-concepts/blob/master/height_weight.ipynb\n   * https://github.com/noahgift/or/blob/master/README.md#randomized-start-with-greedy-path-solution-for-tsp\n\n###   Chapter 3: Machine Learning Deployment In Production ~~Strategies~~\n#### Source Code Chapter 3:\n\n- [Logging Examples](https://github.com/paiml/practical-mlops-book/blob/master/chapter6)\n- [Multiple Loggers](https://github.com/paiml/practical-mlops-book/blob/master/chapter6/multiple-loggers)\n- [Simple Logging](https://github.com/paiml/practical-mlops-book/blob/master/chapter6/simple-logging)\n\n\n###   Chapter 4: Continuous Delivery for Machine Learning Models\n#### Source Code Chapter 4:\n\n###   Chapter 5: AutoML\n#### Source Code Chapter 5:\n\n* [Apple CreateML Walkthrough](https://github.com/noahgift/Apple-CreateML-AutoML-Recipes)\n* [Ludwig Text Classification](https://github.com/paiml/practical-mlops-book/blob/main/Ludwig.ipynb)\n* [FLAML Hello World](https://github.com/noahgift/flaml-nba)\n* [Model Explainability](https://github.com/noahgift/model-explainability)\n\n###   Chapter 6: Monitoring and Logging for Machine Learning\n#### Source Code Chapter 6:\n\n###   Chapter 7: MLOps for AWS\n#### Source Code Chapter 7:\n\n* [Continuous Delivery for Elastic Beanstalk](https://github.com/noahgift/Flask-Elastic-Beanstalk)\n* [ECS Fargate](https://github.com/noahgift/eks-fargate-tutorial)\n* [AWS ML Certification Exam Guide](https://noahgift.github.io/aws-ml-guide/intro)\n* [AWS Cloud Practitioner Exam Guide](https://awscp.noahgift.com/questions-answers)\n* [Free AWS Cloud Practitioner Course](https://store.paiml.com/aws-cloud-practitioner)\n* [Python MLOps Cookbook](https://github.com/noahgift/Python-MLOps-Cookbook)\n* [Container From Scratch](https://github.com/noahgift/container-from-scratch-python)\n\n###   Chapter 8: MLOps for Azure\n#### Source Code Chapter 8:\n\n###   Chapter 9: MLOps for GCP\n#### Source Code Chapter 9:\n\n* [Project Plan Template](https://github.com/paiml/practical-mlops-book/blob/main/Excel%20Template_Ten%20Week%20Demo%20Schedule.xlsx?raw=true)\n* [GCP from Zero](https://github.com/noahgift/gcp-from-zero)\n* [Kubernetes Hello World](https://github.com/noahgift/kubernetes-hello-world-python-flask)\n* [gcp-flask-ml-deploy](https://github.com/noahgift/gcp-flask-ml-deploy)\n* [serverless cookbook](https://github.com/noahgift/serverless-cookbook)\n\n###   Chapter 10: Machine Learning Interoperability\n#### Source Code Chapter 10:\n\n###   Chapter 11: Building MLOps command-line tools\n#### Source Code Chapter 11:\n\n###   Chapter 12: Machine Learning Engineering and MLOps Case Studies\n#### Source Code Chapter 12:\n\n\n### Community Recipes\n\nThis section includes \"community\" recipes.  Many \"may\" be included in the book if timing works out.\n\n* [Jason Adams: FastAPI Sentiment Analysis with Kubernetes](https://github.com/Jason-Adam/sentiment-service)\n* [James Salafatinos:  Tensorflow.js real-time image classification](https://github.com/james-salafatinos/webcam-ml)\n* [Nikhil Bhargava:  Sneaker Price Predict](https://github.com/nikhil-bhargava/ids-706-fp)\n* [Medical Expenditures](https://github.com/joekrinke15/MLModelDeployment)\n* [Flask Salary Predictor](https://github.com/YisongZou/Flask-Salary-Predictor-with-Random-Forest-Algorithm)\n* [Covid Predictor](https://github.com/jingyi-xie/covid-prediction)\n* [Absenteeism at Work](https://github.com/shangwenyan/IDS721FinalProject)\n* [Chest X-Ray on Baidu](https://github.com/Valarzz/Lung-Health-System)\n* [Streamlit Traffic Detection](https://github.com/YUA1024/YUA1024)\n\n### References\n\n* [Pragmatic AI](https://www.amazon.com/Pragmatic-AI-Introduction-Cloud-Based-Analytics/dp/0134863860)\n* [Python for DevOps](https://www.amazon.com/Python-DevOps-Ruthlessly-Effective-Automation/dp/149205769X)\n* [Cloud Computing for Data](https://paiml.com/docs/home/books/cloud-computing-for-data/)\n\n#### Next Steps:  Take Coursera MLOps Course\n\n![cloud-specialization](https://user-images.githubusercontent.com/58792/121041040-650ca180-c780-11eb-956e-8d1ecb134641.png)\n\n* [Take the Specialization](https://www.coursera.org/learn/cloud-computing-foundations-duke?specialization=building-cloud-computing-solutions-at-scale)\n* [Cloud Computing Foundations](https://www.coursera.org/learn/cloud-computing-foundations-duke?specialization=building-cloud-computing-solutions-at-scale)\n* [Cloud Virtualization, Containers and APIs](https://www.coursera.org/learn/cloud-virtualization-containers-api-duke?specialization=building-cloud-computing-solutions-at-scale)\n* [Cloud Data Engineering](https://www.coursera.org/learn/cloud-data-engineering-duke?specialization=building-cloud-computing-solutions-at-scale)\n* [Cloud Machine Learning Engineering and MLOps](https://www.coursera.org/learn/cloud-machine-learning-engineering-mlops-duke?specialization=building-cloud-computing-solutions-at-scale)\n\n\n* [✨Pragmatic AI Labs builds courses on edX](https://insight.paiml.com/d69)\n* [ 💬 Join our Discord community](https://discord.gg/ZrjWxKay)\n","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaiml%2Fpractical-mlops-book","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpaiml%2Fpractical-mlops-book","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaiml%2Fpractical-mlops-book/lists"}