Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Discusses the influence of Big Data on mobility planning and optimization, exploring its promises and limitations.
Covers the fundamentals of data science, emphasizing breadth over depth and practical application in machine learning and data analysis.
Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.
Explores Singular Value Decomposition and its role in unsupervised learning and dimensionality reduction, emphasizing its properties and applications.
