Machine Learning (ML) is a field of Artificial Intelligence (AI) that focuses on enabling systems to learn from data and improve their performance on specific tasks without explicit programming.

ML involves creating algorithms that can analyze patterns in data and make predictions or decisions based on that analysis.

Key Concepts of ML

1. Learning from Data

Machine learning systems learn by analyzing data, identifying patterns and relationships, and using this information to make predictions or decisions.

2. Algorithms

Algorithms are sets of rules and instructions that a machine follows to process data, learn from it, and make predictions or decisions.

3. Models

A model is the output of a machine learning algorithm after it has been trained on data. Once trained, the model can be used to make predictions on new, unseen data.

4. No Explicit Programming

Unlike traditional programming, where every step is explicitly coded, machine learning algorithms learn from experience (data) and continuously improve their performance over time.

5. ML as a Subfield of AI

Machine Learning (ML) is a subset of Artificial Intelligence (AI). It focuses on creating intelligent systems that can learn from data and adapt over time, similar to how humans learn from experience.

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