Book Image

Machine Learning for Streaming Data with Python

By : Joos Korstanje
Book Image

Machine Learning for Streaming Data with Python

By: Joos Korstanje

Overview of this book

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.
Table of Contents (17 chapters)
1
Part 1: Introduction and Core Concepts of Streaming Data
5
Part 2: Exploring Use Cases for Data Streaming
11
Part 3: Advanced Concepts and Best Practices around Streaming Data
15
Chapter 12: Conclusion and Best Practices

Defining classification

In this chapter, you will discover classification. Classification is a supervised machine learning task in which a model is constructed that assigns observations to a category.

The simplest types of classification models that everybody tends to know are decision trees. Let's consider a super simple example of how a decision tree could be used for classification.

Imagine that we have a dataset in which we have observations about five humans and five animals. The goal is to use this data to build a decision tree that can be used on any new, unseen animal or human.

The data can be imported as follows:

Code Block 6-1

import pandas as pd
# example to classify human vs animal
#dataset with one variable
can_speak = [True,True,True,True,True,True,True,False,False,False]
has_feathers = [False,False,False,False,False,True,True,False,False,False]
is_human = [True,True,True,True,True,False,False,False,False,False]
data = pd.DataFrame...