Several fields of materials science, including the production of new and unique materials and enhanced molecular simulations, have benefited from machine learningMachine learning (ML) advancements, and there are probably many more significant advances which are yet to come. It is difficult to comprehend the range of opportunities and the best strategies for using them given the quick developments in this industry. The core of materials science research is finding and comprehending new materials with desirable qualities, and machine learningMachine learning (ML) has provided unique ways to get the end-result. Additionally, the entire range of physical sciences including materials science, has been profoundly impacted by the emergence of big data and algorithmic advancements in machine learningMachine learning (ML). The capabilities of object detection, classification, and segmentation are improved when machine learningMachine learning (ML) is combined with image processing, which transforms the visual information processing in a variety of industries. Technological developments have allowed for the precise extraction of data and the prediction of attributes down to the atomic level, providing previously unattainable insights into materials. In this chapter, we have given an insight to the various machine learningMachine learning (ML) techniques that are employed in the field of materials science along with various aspects of materials science where these techniques have recently had a big impact.