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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mlops-real-world-machine-learning-projects-for-professional/
课程评论：没有评论
**MLOps: 专为专业人士打造的真实世界机器学习项目课程** 本课程是 Coursera 上一门高度实践性的 MLOps 课程，旨在帮助专业人士掌握真实世界机器学习的部署。您将通过构建和部署生产级别的机器学习流水线，学习使用 MLflow, DVC, Docker, Flask, GitHub Actions 和 AWS 等现代工具栈。课程还将展示如何将 ML 模型集成到 Chrome 插件中，全面展示 MLOps 的实际应用。 **主要项目包括：** * **ML Sentiment Analyzer with MLflow & DVC:** 使用 MLflow 和 DVC 构建机器学习情感分析器。 * **Reproducible training pipeline with DVC + Git:** 利用 DVC 和 Git 构建可复现的训练流水线。 * **MLflow tracking dashboard with metrics & artifacts:** 创建一个包含指标和工件的 MLflow 跟踪仪表板。 * **Dockerized inference service with REST API:** 使用 Docker 和 REST API 构建推理服务。 * **End-to-end CI/CD with GitHub Actions:** 通过 GitHub Actions 实现端到端的 CI/CD。 * **Live deployment on AWS EC2:** 将模型实时部署到 AWS EC2。 * **Chrome Extension that calls your ML API in real time:** 构建一个实时调用您的 ML API 的 Chrome 扩展程序。 **课程亮点：** * 获得现代 MLOps 工具的实战经验。 * 学习如何管理数据集、跟踪模型并部署到生产环境。 * 理解应用于机器学习的真实 DevOps 实践。 * 构建可部署的、全栈的机器学习项目作品集。 * 为 MLOps、数据工程和 ML 工程等职位获得就业技能。 本课程将引导您完成一系列模拟真实业务场景的生产级 ML 项目，整合 MLOps 的工具和框架。无论您是希望成为 MLOps 专家，还是首次专业部署模型，本课程都将为您提供所需的知识、代码和系统设计，助您取得成功。
Welcome to the most hands-on and practical MLOps course designed for professionals looking to master real-world machine learning deployment.In this course, you won't just learn theory - you'll build and deploy production-grade ML pipelines using a modern stack including MLflow, DVC, Docker, Flask, GitHub Actions, and AWS. You'll even integrate ML models into a Chrome plugin, showcasing end-to-end MLOps in action.Projects You'll Build:- ML Sentiment Analyzer with MLflow & DVC- Reproducible training pipeline with DVC + Git- MLflow tracking dashboard with metrics & artifacts- Dockerized inference service with REST API- End-to-end CI/CD with GitHub Actions- Live deployment on AWS EC2- Chrome Extension that calls your ML API in real timeWhy Take This Course?Get hands-on experience with modern MLOps toolsLearn how to manage datasets, track models, and deploy to productionUnderstand real-world DevOps practices applied to Machine LearningBuild a portfolio of deployable, full-stack ML projectsGain job-ready skills for roles in MLOps, Data Engineering, and ML EngineeringThroughout this course, you'll work on production-grade ML projects that simulate real business use cases, incorporating tools and frameworks of MLOps. Whether you're looking to become an MLOps expert or deploy your first model professionally, this course equips you with the knowledge, code, and system design needed to succeed.
