Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Automated Machine Learning with Microsoft Azure
  • Toc
  • feedback
Automated Machine Learning with Microsoft Azure

Automated Machine Learning with Microsoft Azure

By : Dennis Michael Sawyers , Dennis Sawyers
4.9 (18)
close
Automated Machine Learning with Microsoft Azure

Automated Machine Learning with Microsoft Azure

4.9 (18)
By: Dennis Michael Sawyers , Dennis Sawyers

Overview of this book

Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK). First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems. By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect.
Table of Contents (17 chapters)
close
1
Section 1: AutoML Explained – Why, What, and How
5
Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide
10
Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions

Chapter 10: Creating End-to-End AutoML Solutions

Now that you have created machine learning (ML) pipelines, you can learn how to use them in other Azure products outside of the Azure Machine Learning Service (AMLS). Perhaps the most useful is Azure Data Factory.

Azure Data Factory (ADF) is Azure's premier code-free data orchestration tool. You can use ADF to pull data from on-premise sources into the Azure cloud, to run ML pipelines, and push data out of Azure by creating an Azure Data Factory pipeline (ADF pipeline). ADF pipelines are an integral part of creating end-to-end ML solutions and are the end goal of any non-real-time AutoML project.

You will begin this chapter by learning how to connect AMLS to ADF. Once you have accomplished this task, you will learn how to schedule an ML pipeline using the parallel pipeline you created in Chapter 9, Implementing a Batch Scoring Solution.

Next, you will learn how to pull data from your local machine and load it into the...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete