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

Prepping data for AutoML forecasting

Forecasting is very different from either classification or regression. ML models for regression or classification predict some output based on some input data. ML models for forecasting, on the other hand, predict a future state based on patterns found in the past. This means that there are key time-related details you need to pay attention to while shaping your data.

For this exercise, you are going to use the OJ Sales Simulated Data Azure Open Dataset for forecasting. Similar to the Diabetes Sample Azure Open Dataset you used for regression, OJ Sales Simulated Data is available simply by having an Azure account. You will use this data to create a model to predict future orange juice sales across different brands and stores.

There is one additional key difference; OJ Sales Simulated Data is a file dataset instead of a tabular dataset. While tabular datasets consist of one file containing columns and rows, file datasets consist of many files...

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