Data science & machine learning are closely related concepts but with a different & specific purpose. The key objective of machine learning is to provide an implementation layer to artificial intelligence concepts. The speciality in machine learning systems as opposed to conventional applications is that ML applications are not extensively instructed by codes. Rather, they self-learn from the trends and patterns of data without any human intervention. For example – solutions such as smart homes, recommendation engines etc. are perfect examples of machine learning algorithms.
Data science is more intrinsically linked with extraction, cleansing and analysis of data to derive business insights out of it. There is definite overlap between the two as machine learning algorithms self-learn from data itself.