December 2024
Intermediate to advanced
170 pages
4h 11m
English
book
Machine Learning in Transportation
by Niharika Dayyala, Nivedya Madankara Kottayi, Rajib Basu Mallick
Content preview from Machine Learning in Transportation
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Chapter 2 Preliminary steps for machine learning
2.1 Introduction
In this chapter, we focus on the preliminary steps for machine learning including getting the software, loading the data, exploring the data, cleaning the data, transformation, and data visualization.
The process of exploring, cleansing, and transforming data is called “data wrangling.” It is one of the essential steps a transportation data analyst needs to perform prior to performing data analysis. The data wrangling process enriches transportation data to support further data analysis. It improves the quality of data, which in turn helps extract true insights from the data. Although data wrangling is a time-consuming activity, it can bring forth the true power of data.
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