Material science and machine learning (ML) are two vital interdisciplinary fields in many businesses, from energy storage and electronics to healthcare. Materials science covers many industries because materials make up everything around us. At the same time, machine learning as a subfield of computer science and artificial intelligence (AI) is an active and exciting area for research and development. Therefore, a collaboration between ML and material science makes a framework at the center of developing the next generation of materials and material systems that will power modern innovations. Moreover, material science and machine learning are powerful tools to tackle real-world challengesChallenges in machine learning in all scientific fields. The recent successes of machine learning algorithms such as deep learning(DL)Deep Learning (DL) have given material scientists and engineers a unique opportunity. Machine learning algorithms can assist material researchers in data mining and extracting hidden information from materials data. This chapter investigates the diverse applications of ML algorithms in materials science. It provides insight into data-driven material discoveryMachine learning in material discovery and the transformative potential of ML in material science without detailed algorithms and mathematical equations.