May 2019
Beginner to intermediate
288 pages
9h 1m
English
book
Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
by Andrew Kelleher, Adam Kelleher
Content preview from Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
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4. Data Encoding and Preprocessing
4.1 Introduction
Data preprocessing is an important step in machine learning. It’s the first step and a place where there is a lot of room for subjective decision-making, which can reduce the information content of your data in ways you’ll learn about in this chapter.
Generally, data preprocessing is the process of mapping raw data into a format that is ready to pass into a machine-learning algorithm. You can assume for now that there’s no uncertainty in the data that you’re encoding, and you’ll revisit the problem of uncertainty in later chapters. For now, you’ll learn how you can encode measurements in a way an algorithm can understand. You can also take steps to make sure your models perform as well as ...
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