MLOps Tools: MLflow and Hugging Face

سرفصل های دوره

In this course, learn how to master MLflow and Hugging Face, two powerful open-source platforms for MLOps. Starting with MLflow, learn how to streamline the machine learning lifecycle, manage projects and models, use the tracking UI system, and interact with registered models. Then, get an introduction to Hugging Face, starting with an overview of the Hugging Face Hub, repositories, and Hugging Face Spaces. Learn how to collaborate and deploy models, store datasets and models, create live interactive demos, and leverage community repositories.

Note: This course was created by Pragmatic AI Labs. We are pleased to host this training in our library

01 - Introduction

01 - MLOps platforms introduction

02 - 1. Introduction to MLflow

01 - Overview of MLflow

02 - Installing and using MLflow

03 - Introduction to the tracking UI

04 - Parameters, version, artifacts, and metrics

03 - 2. MLflow Projects

01 - Working with MLflow projects

02 - Create an MLflow project

03 - Run projects from remote Git repositories

04 - Connecting MLflow to Databricks

04 - 3. MLflow Models

01 - Components of the MLflow package

02 - Use a registry with an MLflow model

03 - Referencing artifacts with the API

04 - Saving and serving MLflow models

05 - 4. Introduction to Hugging Face

01 - What is Hugging Face

02 - Overview of the Hugging Face Hub

03 - Introduction to the Hugging Face Hub

04 - Using Hugging Face repositories

05 - Using Hugging Face Spaces

06 - 5. Introduction to Applied Hugging Face

01 - Introduction to applied Hugging Face

02 - Using GPU-enabled Codespaces

03 - Using the Hugging Face CLI

07 - 6. Using Hugging Face

01 - Using the Model Hub

02 - Downloading models

03 - Working with models

04 - Adding datasets

05 - Using datasets

06 - Working with datasets

08 - 7. Packaging Hugging Face

01 - Hugging Face and FastAPI

02 - Containerizing Hugging Face

03 - Running FastAPI with Hugging Face

04 - CICD packaging with GitHub Actions

09 - 8. Hugging Face and Azure ML Studio

01 - Hugging Face and Azure ML Studio

02 - Registering a Hugging Face dataset on Azure

03 - Registering a Hugging Face model on Azure

04 - Inspecting a Hugging Face dataset on Azure

05 - Azure ML Python SDK

10 - 9. Hugging Face Automation

01 - Using GitHub Actions for model deployments

02 - Using Azure Container Registry

03 - Automating packaging with Azure Container Registry

04 - Automating packaging Docker Hub

11 - 10. Hugging Face with Azure Containers

01 - Create an Azure container application

02 - Configure an Azure container application

03 - Deploy Hugging Face to Azure

04 - Troubleshooting container deployment

12 - 11. Fine-Tuning and ONNX Exporting

01 - Introduction to fine-tuning theory

02 - Performing fine-tuning

03 - Introduction to ONNX and Hugging Face

04 - Exporting Hugging Face models to ONNX

13 - 12. Hugging Face Spaces

01 - Introduction to Hugging Face Spaces

02 - Hugging Face Spaces walkthrough

03 - Deploying to Hugging Face Spaces

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تولید کننده: LinkedIn Learning (Lynda)