Initially, computers were used to the run programs or specific set of the instruction which basically are pre-defined by a programmer. Programs are written in the higher level languages by programmers, compiled down to binary code by operating systems to run set of instructions.
Eventually, this lead to new descipline of computer science called “Artificial Intelligence”. Artificial Intelligence is field of computer science which deals with theory and development of computer systems and programs which allow to perform tasks which normally requires human intelligence. Machine learning is th sub-category of the Artifiical Intelligence. In my mind, AI is higher level abstraction and Machine learning is one the implementation for AI.
What is Machine Learning?
Machine Learning is the general term for when computers learn from data. It is ability of computer to learn from the data without being explicity programmed to that. It describes the intersection of computer science and statistics where algorithms are used to perform a specific task without being explicitly programmed; instead, they recognize patterns in the data and make predictions once new data arrives.
Tom Mitchell has summarized the machine learning really well. In his words , “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”
Following Image explains the abstractions of artificial intelligence and explains the how ai, machine learning counter parts are linked.
