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Designing Machine/Deep Learning Models Using Azure CLI

Name: Designing Machine/Deep Learning Models Using Azure CLI
Price: 59 USD
Author: Soudamini Sreepada

Gain insights into Azure basics, build ML/deep learning pipelines, manage deployments, and analyze models ethically with responsible AI, ensuring fairness and bias mitigation.

34 lessons

3 projects

10h

Created by Soudamini Sreepada

Designing Machine/Deep Learning Models Using Azure CLI

What's included

34 lessons across 8 modules
3 quizzes with instant feedback
3 projects in preconfigured environments
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

A working knowledge of Azure CLI for machine/deep learning
Hands-on experience building and scheduling machine/deep learning pipelines
The ability to deploy deep learning models using distributed training
An understanding of MLflow integration with Azure Machine Learning
A working knowledge of responsible AI using Azure Machine Learning

Learning Roadmap

34 Lessons3 Projects3 Quizzes

Introduction

Learn how to use Azure's services, CLI tools, and comprehensive machine learning capabilities.

Introduction to Azure

Introduction to Azure CLI

Introduction to Azure Machine Learning

Getting Started

Look at setting up Microsoft and Azure accounts and using Azure CLI commands.

Creating a Microsoft Account

Signing Up With Azure

Azure CLI Commands Help

Quiz on Azure Installations

Creating Azure Resources

8 Lessons

Work your way through creating Azure resources, including YAML, resource groups, VMs, and storage.

Building Azure ML Pipeline

6 Lessons

Grasp the fundamentals of creating Azure ML pipelines, managing datasets, and optimizing models.

Building a diabetes model pipeline

Project

Service Deployment

6 Lessons

Take a closer look at deploying, testing, and managing machine learning models in Azure.

Creating a Deep Learning Pipeline

5 Lessons

Follow the process of creating and deploying efficient and equitable deep learning models on Azure.

Detect Posture Project

Project

Conclusion

Build on Azure ML's features for pipelines, cost management, reproducibility, and Responsible AI.

Wrap Up!

Appendix

Learn how to use Azure CLI setup and installation across different operating systems.

Setup and Installation

Sentiment Analysis Using Natural Language Processing

Project

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

In this course, you will start your journey by gaining a comprehensive understanding of the basics of Azure, including creating and managing Azure resources, and setting up the Azure CLI environment. Next, you will learn how to build Azure Machine Learning pipelines from scratch. Then, you’ll delve into deep learning and distributed deep learning pipelines. You’ll learn how to manage the deployment and scheduling of these models. You’ll also cover the complete model management strategies. Finally, the course will cover model analysis using responsible AI, teaching how to identify and mitigate potential biases in models and ensuring that models are ethical and fair. You’ll also learn how to analyze the models and identify potential areas for improvement. By the end of this course, you’ll have a comprehensive understanding of Azure Machine Learning, including how to build complex pipelines, deploy models using online/batch methods, and manage and analyze models using tools like MLflow and responsible AI.

ABOUT THE AUTHOR

Soudamini Sreepada

Principal Data Scientist, Mentor, Instructor with 18 years of experience with Microsoft R & D, India. Part of shipping multiple products like Data Protection Manager, windows-7, Bing from inception. Shipped multiple ML/DL products at scale.

Learn more about Soudamini

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