Machine learning algorithms require that data is formatted and presented in very specific ways. In this course, Preparing Data for Machine Learning with Java, you’ll learn to use the standard Java API to make data ready for ML libraries. First, you’ll explore various options to read files into Java objects and data structures. Next, you’ll discover how to scrape the web for data you could use in your ML models. Finally, you’ll learn how to perform transformation both in vanilla Java and at scale with the Beam SDK. When you’re finished with this course, you’ll have the skills and knowledge of data gathering needed to digitize various sources into Java data structures.
Author Name: Federico Mestrone
Author Description:
Also known as Fed in the English-speaking world, Federico has an intriguing eclectic approach to technology. In love with it since he was 12 – back in the days of the Commodore 64 – he betrays it on a regular basis: first with ballet and contemporary dance, then with synchronised swimming, recently with Japanese language and culture. Mostly a Java/Scala developer and Linux/Mac OS user, over the course of 20+ years he has had commercial experience in several other platforms and programming langua… more

Table of Contents

• Course Overview
  1min
• Ingesting Data from Files in Various Formats
  19mins
• Automating Data Collection and Scheduling
  33mins
• Data Cleaning Using Regex and Formatter
  22mins
• Data Transformation
  19mins
• Data Preparation at Scale
  26mins