Learning From Data | Vibepedia

Learning from data is a fundamental concept in machine learning, a field of study in artificial intelligence that focuses on developing statistical algorithms that can learn from data and generalize to unseen data. With the help of deep learning, a subdiscipline of machine learning, neural networks have surpassed many previous machine learning approaches in performance. The foundations of machine learning are composed of statistics and mathematical optimization methods, with data mining being a related field of study that focuses on exploratory data analysis through unsupervised learning. Probably approximately correct learning provides a mathematical and statistical framework for describing machine learning, with most traditional machine learning and deep learning algorithms being described as empirical risk minimization. As of 2024, companies like [[google|Google]] and [[microsoft|Microsoft]] are heavily investing in machine learning research, with applications in [[natural-language-processing|natural language processing]] and [[computer-vision|computer vision]]. The use of machine learning has also raised concerns about [[bias-in-ai|bias in AI]] and the need for [[explainable-ai|explainable AI]]. With the increasing amount of data being generated, the importance of learning from data will only continue to grow, with potential applications in [[healthcare|healthcare]], [[finance|finance]], and [[education|education]].