ABSTRACT
Due to continued urbanization and modernization, smart cities have become our future. In smart cities, it is of significance to harness the technologies to create advanced lifestyles at an affordable cost sustainably. For reaching this level of growth, a huge volume of data is required, i.e., big data which is prone to errors and can be of labelled and unlabelled type. To leverage this data for development, machine learning plays a huge role. The use of machine learning depends on the data being labelled for supervised learning to find specific solutions in the collected raw data or unlabelled for unsupervised learning to find solutions by recognizing underlying patterns/anomalies.
This chapter focuses on advanced machine learning algorithms and their ability to handle the diverse data collected efficiently to provide solutions. Also, the applications of these algorithms in a smart city like traffic management, pollution control, energy conservation, healthcare and public security will be of concern here.
