This is the code repository for Automated Machine Learning with Microsoft Azure, published by Packt.

Build highly accurate and scalable end-to-end AI solutions with Azure AutoML

Automated Machine Learning with Microsoft Azure helps you build high-performing, accurate machine learning models in record time. It allows anyone to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. With a series of clicks on a guided user interface (GUI), novices and seasoned data scientists alike can easily train and deploy machine learning solutions to production.

This book covers the following exciting features:

• Get to grips with building automated machine learning models
• Build classification and regression models with impressive accuracy in a short time
• Develop neural network classifiers with AutoML techniques
• Compare AutoML models with traditional, manually developed models on the same datasets
• Create robust, production-ready models

If you feel this book is for you, get your copy today!

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

from azureml.core import Workspace, Dataset, Datastore
from azureml.core import Experiment
from azureml.core.compute import ComputeTarget
from azureml.train.automl import AutoMLConfig
from azureml.train.automl.run import AutoMLRun

Following is what you need for this book: Data scientists, aspiring data scientists, machine learning engineers, or anyone interested in applying artificial intelligence or machine learning in their business will find this book useful. You need to have beginner-level knowledge of artificial intelligence and a technical background in computer science, statistics, or information technology before getting started with this machine learning book. Having a background in Python will help you implement this book’s more advanced features, but even data analysts and SQL experts will be able to train ML models after finishing this book.

With the following software and hardware list you can run all code files present in the book (Chapter 1-12).

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

• Automated Machine Learning [Packt] [Amazon]

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Dennis Michael Sawyers is a Senior Cloud Solutions Architect at Microsoft, specializing in Data and Artificial Intelligence. In his role as a CSA, he helps Fortune 500 Companies leverage Microsoft Azure cloud technology to build top-class machine learning and AI solutions. Prior to his role at Microsoft, he was a Data Scientist at Ford Motor Company in Global Data Insights & Analytics (GDIA) and a researcher in anomaly detection at the highly regarded Carnegie Mellon Auton Lab. He received a master’s degree in Data Analytics from Carnegie Mellon's Heinz College and a bachelor’s degree from the University of Michigan. More than anything, Dennis is passionate about democratizing AI solutions through automated machine learning technology.