The book "Machine Learning in Transportation Applications with Examples and Codes" provides a comprehensive overview of the application of machine learning techniques in transportation systems, including traffic prediction, route planning, and autonomous vehicles. The book covers the fundamental concepts of machine learning and their applications in various transportation domains such as road, rail, air, and sea. It also discusses the challenges and limitations of these techniques and provides examples and codes to help readers understand the practical implementation of these methods. The book begins by introducing the concept of machine learning and its importance in transportation systems. It highlights the need for developing a personal paradigm for understanding the technological process of developing modern knowledge as the basis for the survival of humanity and the survival of the unification of people in a warring state. The author emphasizes the significance of studying and understanding the evolution of technology and its impact on society. The book then delves into the various applications of machine learning in transportation, starting with traffic prediction, which is critical for optimizing traffic flow and reducing congestion.

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