Machine learning is a subset of artificial intelligence (AI) that focuses on the development of [[machine learning algorithm|machine learning algorithms]] and [[machine learning model|machine learning models]] that enable computers to learn from and make predictions or decisions based on data. Instead of being explicitly programmed to perform a specific task, machine learning systems use data to learn patterns, make predictions, and improve their performance over time. The core idea behind machine learning is to allow computers to learn from examples and data, rather than being explicitly programmed with specific rules. This is achieved through the use of algorithms that enable machines to recognize patterns, identify trends, and make informed decisions based on the data they've been trained on. Machine learning involves several key concepts: [[dataset]], [[input feature]], [[label]], [[training]], [[validation]], [[testing]], [[supervised learning]], [[unsupervised learning]], [[semi-supervised learning]], and [[reinforcement learning]]. [[artificial intelligence]] < [[Hands-on LLMs]]/[[1 Machine Learning Basics]] > [[dataset]]