Open access peer-reviewed Edited Volume

Introduction to Data Science and Machine Learning

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13,046 Chapter Downloads

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Academic Editor

Keshav Sud
Keshav Sud

University of Illinois at Chicago

Co-editors

Pakize Erdogmus
Pakize Erdogmus

Duzce University

Seifedine Kadry
Seifedine Kadry

Noroff University College, Norway

Published25 March 2020

Doi10.5772/intechopen.77469

ISBN978-1-83880-334-6

Print ISBN978-1-83880-333-9

eBook (PDF) ISBN978-1-83880-371-1

Copyright year2020

Number of pages232

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Table of Contents

Open access  chapters

3. Software Design for Success

By Laura M. Castro

740
4. Embedded Systems Based on Open Source Platforms

By Zlatko Bundalo and Dusanka Bundalo

1,198
2
5. The K-Means Algorithm Evolution

By Joaquín Pérez-Ortega, Nelva Nely Almanza-Ortega, Andrea Vega-Villalobos, Rodolfo Pazos-Rangel, Crispín Zavala-Díaz and Alicia Martínez-Rebollar

1,399
15
903
2
822
9. The Software to the Soft Target Assessment

By Lucia Mrazkova Duricova, Martin Hromada and Jan Mrazek

937
10. The Methodological Standard to the Assessment of the Traffic Simulation in Real Time

By Jan Mrazek, Martin Hromada and Lucia Duricova Mrazkova

904
12. Serialization in Object-Oriented Programming Languages

By Konrad Grochowski, Michał Breiter and Robert Nowak

1,864
3

IMPACT OF THIS BOOK AND ITS CHAPTERS

13,046 Total Chapter Downloads

29 Crossref Citations

2 Web of Science Citations

47 Dimensions Citations

4 Altmetric Score

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