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Machine Learning in Transportation

Applications with Examples and Codes

Niharika Dayyala, Nivedya Madankara Kottayi, Rajib Basu Mallick (Autoren)

Buch | Softcover

VII, 163 Seiten

2024
De Gruyter (Verlag)
978-3-11-078866-2 (ISBN)

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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.

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

Erscheinungsdatum	05.12.2024
Reihe/Serie	De Gruyter Textbook
Zusatzinfo	b/w maps
Verlagsort	Berlin/Boston
Sprache	englisch
Maße	170 x 240 mm
Gewicht	299 g
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Technik ► Fahrzeugbau / Schiffbau
	Technik ► Maschinenbau
Schlagworte	Artificial Intelligence • Building construction & materials • Business & Economics • BUSINESS & ECONOMICS / Industries • BUSINESS & ECONOMICS / Industries / Computers & Information Technology • classical mechanics • COM004000 COMPUTERS / Intelligence (AI) & Semantics • Computers & Information Technology • Computer Science • Computer sciences • COMPUTERS / Intelligence (AI) & Semantics • Fundamentals of Mechanical Engineering • General Studies • impact of science & technology on society • interdisciplinary studies • machine learning • Materials • mechanical engineering • mechanical engineering & materials • Mechanical engineering and materials • Reference, information & interdisciplinary subjects • Science • SCIENCE / General • Science: general issues • Technik • Technology & Engineering / Civil • Technology & Engineering / Civil / General • Technology & Engineering / Mechanical • Technology, Engineering, Agriculture, Industrial processes • Transportation.
ISBN-10	3-11-078866-7 / 3110788667
ISBN-13	978-3-11-078866-2 / 9783110788662
Zustand	Neuware