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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
课程评论：没有评论
课程名称：MLOps工具：MLflow与Hugging Face 概述：本课程涵盖了当前最流行的两个开源MLOps（机器学习操作）平台：MLflow和Hugging Face。课程内容包括如何在这两个平台上开始进行基本的模型和数据集操作。您将首先学习如何使用MLflow进行项目和模型管理，充分利用其强大的跟踪系统，然后通过完整的生命周期示例学习如何与MLflow中注册的模型进行交互。接着，您将探索Hugging Face的代码库。 课程大纲： 1. **MLflow简介** - 描述：本模块将介绍MLflow及其使用方法。您将安装MLflow并执行基本操作，如注册运行、模型和工件。接着，创建一个可复现结果的MLflow项目，并理解如何使用MLflow模型的注册表及通过API引用工件。 2. **Hugging Face简介** - 描述：在本模块中，您将学习Hugging Face平台的基本知识。将利用其仓库功能存储模型和数据集，最后学习如何使用Hugging Face API及其网页界面添加和使用模型和数据集。 3. **Hugging Face模型部署** - 描述：该模块将教您如何将Hugging Face模型容器化，并使用FastAPI框架为模型提供一个交互式HTTP API端点。掌握整合流程后，您将利用自动化提高速度和可重复性，并使用Azure和Docker Hub存储容器，以便后续部署。 4. **应用Hugging Face** - 描述：在本模块中，您将学习如何通过使用现有模型并添加数据对Hugging Face模型进行微调。同时，您将利用Azure进行容器部署，并学习如何对其进行故障排除。最后，还将展示如何将模型部署到Hugging Face空间。 通过本课程，您将获得使用MLflow与Hugging Face进行MLOps的实践经验，提高您在机器学习项目中的部署和管理能力。
Name:Introduction to MLflow
Description:In this module, you will learn what MLflow is and how to use it. You’ll install MLflow and perform basic operations like registering runs, models, and artifacts. Then, you’ll create an MLflow project for reproducible results. Finally, you’ll understand how to use a registry with MLflow models and reference artifacts from the API.
Name:Introduction to Hugging Face
Description:In this module, you will learn the basics of the Hugging Face platform. You will use some of its features like its repositories so that you can store models and datasets. Finally, you will learn how to add and use models and datasets using Hugging Face APIs as well as the web interface.
Name:Deploying Hugging Face
Description:In this module, you will learn how to containerize Hugging Face models and use the FastAPI framework to serve the model with an interactive HTTP API endpoint. Once you understand how to put everything together, you’ll use automation for speed and reproducibility. Finally, you’ll use Azure and Docker Hub to store the containers so that they can be used later for deployments.
Name:Applied Hugging Face
Description:In this module, you will learn how to fine-tune Hugging Face models by using pre-existing models and then modifying (fine-tuning) them with additional data. You’ll also use Azure to deploy the container and learn how to troubleshoot it. Finally, you’ll also see how to deploy a model to Hugging Face spaces.
This course covers two of the most popular open source platforms for MLOps (Machine Learning Operations): MLflow and Hugging Face. We’ll go through the foundations on what it takes to get started in these platforms with basic model and dataset operations. You will start with MLflow using projects and models with its powerful tracking system and you will learn how to interact with these registered models from MLflow with full lifecycle examples. Then, you will explore Hugging Face repositories so
