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Machine Learning for Streaming Data with Python

Machine Learning for Streaming Data with Python

By : Joos Korstanje
4.2 (9)
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Machine Learning for Streaming Data with Python

Machine Learning for Streaming Data with Python

4.2 (9)
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)
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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

Demystifying the HTTP protocol

Interaction between services (or websites) uses the HTTP protocol. When working with APIs and building communicating microservices, it is important to understand the basics of the HTTP protocol.

The most important thing to know is how to send and format requests and responses.

The GET request

The simplest HTTP request is the GET request. You use this when you need to get something from a server or a service. For example, when going to a website, your browser sends a GET request to the website's IP address to obtain the website's layout code.

A GET request can simply be sent from Python using the following code:

Code block 2-2

import requests
import json
response = requests.get('http://www.google.com')
print(response.status_code)
print(response.text)

This code uses the requests library in Python to send a GET request to the Google home page. This is technically the same process as...

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