In Machine Learning (ML), computers efficiently adapt data and solve new problems that are related to previously encountered problems. This allows machines to perform useful exploratory and predictive tasks such as natural language understanding and anomaly detection, without being explicitly programmed. This course covers the theoretical foundations and practical applications of ML and the design, implementation, and analysis of various ML algorithms.
You will learn how to choose, design, and implement the most appropriate ML algorithms for various problem types. If you know a programming language, probability, and some linear algebra, this course is for you! It can adequately prepare you for a career in both industry & academia.
You may have heard the phrase, a man is known by the company it keeps, similarly a data set is known by the company it keeps!