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Machine Learning (ML)

Machine Learning (ML) is the subset of artificial intelligence (AI) that focuses on building systems that learn—or improve performance—based on the data they consume. Artificial intelligence is a broad term that refers to systems or machines that mimic human intelligence.

Machine learning is an application of AI that enables systems to learn and improve from experience without being explicitly programmed.

Machine learning and AI are often discussed together, and the terms are sometimes used interchangeably, but they don’t mean the same thing. An important distinction is that although all machine learning is AI, not all AI is machine learning.

Supervised Machine Learning: Supervised machine learning algorithms are the most commonly used. With this model, a data scientist acts as a guide and teaches the algorithm what conclusions it should make. .

Unsupervised Machine Learning: Unsupervised machine learning uses a more independent approach, in which a computer learns to identify complex processes and patterns without a human providing close, constant guidance. Unsupervised machine learning involves training based on data that does not have labels or a specific, defined output.

The three types of learning in machine learning:

There are three machine learning types: supervised, unsupervised, and reinforcement learning.