Machine Learning in Transportation Applications with Examples and Codes

The book introduces the reader to machine learning in transportation. It discusses both simple and advanced concepts including core statistics, data wrangling, data visualization, supervised and unsupervised datamining techniques as well as text mining. The book prepares students to manage data, visualize data and apply appropriate machine learning techniques on transportation datasets to derive important insights.

About the author

Niharika Dayyala,
Illinois State Uni.
, Nivedya M. Kottayi
, San Diego Association of Governments,
Rajib B. Mallick
, Uni. of Texas, USA.

Summary

The book introduces the reader to machine learning in transportation. It discusses both simple and advanced concepts including core statistics, data wrangling, data visualization, supervised and unsupervised datamining techniques as well as text mining. The book prepares students to manage data, visualize data and apply appropriate machine learning techniques on transportation datasets to derive important insights.

Product details

• Authors: Rajib B. Mallick, Niharika Dayyala, Rajib Basu Mallick, Malli, Rajib B Mallick, Nivedya Madankara Kottayi
• Publisher: De Gruyter
• Content: Book
• Product form: Paperback / Softback
• Publication date: 01.01.2025
• Subject: Natural sciences, medicine, IT, technology > Technology
• EAN: 9783110788662
• ISBN: 978-3-11-078866-2
• Pages: 163
• Illustrations: 4 b/w and 61 col. ill., 7 b/w tbl., 1 b/w maps
• Dimensions (packing): 17 x 24 cm
• Weight (packing): 299 g
• Series: De Gruyter Textbook
• Subjects: Informatik, machine learning, Artificial Intelligence, Verkehrstechnik und Transportwesen, SCIENCE / General, Textbook, TECHNOLOGY & ENGINEERING / Civil / General, materials, Classical mechanics, Computer Sciences, Impact of science & technology on society, Building construction & materials, General studies, SCI000000 SCIENCE / General, Technology, Engineering, Agriculture, Industrial processes, Mechanical engineering and materials, COM004000 COMPUTERS / Intelligence (AI) & Semantics, TEC009020 Technology & Engineering / Civil / General, BUSINESS & ECONOMICS, Transportation., Fundamentals of Mechanical Engineering