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- Machine learning - Wikipedia
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data, and thus perform tasks without explicit instructions [1]
- What is machine learning? - IBM
Machine learning is the subset of AI focused on algorithms that analyze and “learn” the patterns of training data in order to make accurate inferences about new data
- Machine Learning Tutorial - GeeksforGeeks
Machine learning is a branch of Artificial Intelligence that focuses on developing models and algorithms that let computers learn from data without being explicitly programmed for every task In simple words, ML teaches the systems to think and understand like humans by learning from the data
- What Is Machine Learning? Definition, Types, and Examples
Machine learning is a subfield of artificial intelligence (AI) that uses algorithms trained on data sets to create self-learning models capable of predicting outcomes and classifying information without human intervention
- Machine Learning | Google for Developers
An introduction to the characteristics of machine learning datasets, and how to prepare your data to ensure high-quality results when training and evaluating your model
- Machine learning, explained - MIT Sloan
What is machine learning? Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems
- What Is Machine Learning? - Britannica
Machine learning is a process that enables computers to learn autonomously by identifying patterns and making data-based decisions
- What Is Machine Learning? Key Concepts and Real-World Uses
Machine learning refers to the process by which computers are able to recognize patterns and improve their performance over time without needing to be programmed for every possible scenario Instead of following a rigid set of rules, these systems analyze data, make predictions, and adjust their approach based on their learning
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