Definitions of ML[1]#
Machine learning is a field of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computer systems to improve their performance on a specific task through learning from data, without being explicitly programmed. There are several popular definitions of machine learning.
Arthur Samuel’s Definition (1959)
The field of study that gives computers the ability to learn without being explicitly programmed.
Tom Mitchell’s Definition (1997)
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 \(E\).
This definition provides a more formal framework for understanding machine learning, emphasizing the improvement in task performance through learning.
Arthur Samuel’s Practical Definition:
Arthur Samuel also offered a practical definition of machine learning as “the ability to improve the performance of a task by being exposed to data.
This definition underscores the practical aspect of machine learning, where algorithms improve their performance by processing and learning from data.
Modern Definition
A field of AI that uses statistical techniques and algorithms to enable computer systems to recognize patterns in data, make predictions, classify information, and automate decision-making based on the learned patterns and insights.
These definitions collectively capture the core idea of machine learning, which is the ability of computers to learn from data and adapt their behavior or performance on specific tasks.