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Machine learning (ML) techniques refer to a set of algorithms and methods used to enable computers to learn from data and improve their performance over time without being explicitly programmed. These techniques include supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, models are trained on labeled data to make predictions or classifications based on input-output pairs. Unsupervised learning involves training models on unlabeled data to discover patterns or structures within the data. Reinforcement learning focuses on learning optimal decision-making strategies through interaction with an environment and receiving feedback in the form of rewards or penalties. Machine learning techniques have gained prominence in recent years due to advances in computational power, availability of large datasets, and improvements in algorithmic efficiency, leading to their widespread adoption in various fields such as healthcare, finance, marketing, and autonomous systems.
References: - https://en.wikipedia.org/wiki/Machine_learning