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Implement machine learning, cognitive services, and artificial
intelligence solutions by leveraging Azure cloud technologies Key
Features Learn advanced concepts in Azure ML and the Cortana
Intelligence Suite architecture Explore ML Server using SQL Server
and HDInsight capabilities Implement various tools in Azure to
build and deploy machine learning models Book
DescriptionImplementing Machine learning (ML) and Artificial
Intelligence (AI) in the cloud had not been possible earlier due to
the lack of processing power and storage. However, Azure has
created ML and AI services that are easy to implement in the cloud.
Hands-On Machine Learning with Azure teaches you how to perform
advanced ML projects in the cloud in a cost-effective way. The book
begins by covering the benefits of ML and AI in the cloud. You will
then explore Microsoft's Team Data Science Process to establish a
repeatable process for successful AI development and
implementation. You will also gain an understanding of AI
technologies available in Azure and the Cognitive Services APIs to
integrate them into bot applications. This book lets you explore
prebuilt templates with Azure Machine Learning Studio and build a
model using canned algorithms that can be deployed as web services.
The book then takes you through a preconfigured series of virtual
machines in Azure targeted at AI development scenarios. You will
get to grips with the ML Server and its capabilities in SQL and
HDInsight. In the concluding chapters, you'll integrate patterns
with other non-AI services in Azure. By the end of this book, you
will be fully equipped to implement smart cognitive actions in your
models. What you will learn Discover the benefits of leveraging the
cloud for ML and AI Use Cognitive Services APIs to build
intelligent bots Build a model using canned algorithms from
Microsoft and deploy it as a web service Deploy virtual machines in
AI development scenarios Apply R, Python, SQL Server, and Spark in
Azure Build and deploy deep learning solutions with CNTK, MMLSpark,
and TensorFlow Implement model retraining in IoT, Streaming, and
Blockchain solutions Explore best practices for integrating ML and
AI functions with ADLA and logic apps Who this book is forIf you
are a data scientist or developer familiar with Azure ML and
cognitive services and want to create smart models and make sense
of data in the cloud, this book is for you. You'll also find this
book useful if you want to bring powerful machine learning services
into your cloud applications. Some experience with data
manipulation and processing, using languages like SQL, Python, and
R, will aid in understanding the concepts covered in this book
Develop and manage effective real-time streaming solutions by
leveraging the power of Microsoft Azure About This Book * Analyze
your data from various sources using Microsoft Azure Stream
Analytics * Develop, manage and automate your stream analytics
solution with Microsoft Azure * A practical guide to real-time
event processing and performing analytics on the cloud Who This
Book Is For If you are looking for a resource that teaches you how
to process continuous streams of data in real-time, this book is
what you need. A basic understanding of the concepts in analytics
is all you need to get started with this book What You Will Learn *
Perform real-time event processing with Azure Stream Analysis *
Incorporate the features of Big Data Lambda architecture pattern in
real-time data processing * Design a streaming pipeline for storage
and batch analysis * Implement data transformation and computation
activities over stream of events * Automate your streaming pipeline
using Powershell and the .NET SDK * Integrate your streaming
pipeline with popular Machine Learning and Predictive Analytics
modelling algorithms * Monitor and troubleshoot your Azure
Streaming jobs effectively In Detail Microsoft Azure is a very
popular cloud computing service used by many organizations around
the world. Its latest analytics offering, Stream Analytics, allows
you to process and get actionable insights from different kinds of
data in real-time. This book is your guide to understanding the
basics of how Azure Stream Analytics works, and building your own
analytics solution using its capabilities. You will start with
understanding what Stream Analytics is, and why it is a popular
choice for getting real-time insights from data. Then, you will be
introduced to Azure Stream Analytics, and see how you can use the
tools and functions in Azure to develop your own Streaming
Analytics. Over the course of the book, you will be given
comparative analytic guidance on using Azure Streaming with other
Microsoft Data Platform resources such as Big Data Lambda
Architecture integration for real time data analysis and
differences of scenarios for architecture designing with Azure
HDInsight Hadoop clusters with Storm or Stream Analytics. The book
also shows you how you can manage, monitor, and scale your solution
for optimal performance. By the end of this book, you will be
well-versed in using Azure Stream Analytics to develop an efficient
analytics solution that can work with any type of data. Style and
approach A comprehensive guidance on developing real-time event
processing with Azure Stream Analysis
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