Apply machine learning to streaming data with the help of practical
examples, and deal with challenges that surround streaming
Key Features:
-
Work on streaming use cases that are not taught in most data science
courses
-
Gain experience with state-of-the-art tools for streaming data
-
Mitigate various challenges while handling streaming data
Book Description:
Streaming data is the new top technology to watch out for in the field
of data science and machine learning. As business needs become more
demanding, many use cases require real-time analysis as well as
real-time machine learning. This book will help you to get up to speed
with data analytics for streaming data and focus strongly on adapting
machine learning and other analytics to the case of streaming data.
You will first learn about the architecture for streaming and real-time
machine learning. Next, you will look at the state-of-the-art frameworks
for streaming data like River. Later chapters will focus on various
industrial use cases for streaming data like Online Anomaly Detection
and others. As you progress, you will discover various challenges and
learn how to mitigate them. In addition to this, you will learn best
practices that will help you use streaming data to generate real-time
insights.
By the end of this book, you will have gained the confidence you need to
stream data in your machine learning models.
What You Will Learn:
-
Understand the challenges and advantages of working with streaming
data
-
Develop real-time insights from streaming data
-
Understand the implementation of streaming data with various use cases
to boost your knowledge
-
Develop a PCA alternative that can work on real-time data
-
Explore best practices for handling streaming data that you absolutely
need to remember
-
Develop an API for real-time machine learning inference
Who this book is for:
This book is for data scientists and machine learning engineers who have
a background in machine learning, are practice and technology-oriented,
and want to learn how to apply machine learning to streaming data
through practical examples with modern technologies. Although an
understanding of basic Python and machine learning concepts is a must,
no prior knowledge of streaming is required.
