Supervised Learning
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Supervised learning is a type of machine learning where the algorithm is trained on a labeled dataset where each data point has a corresponding label or output value The algorithm learns to map the input data to the desired output allowing it to make predictions for new unseen data Supervised machine learning is based on the following core concepts: Data Model Training Evaluating Inference Data Data is the driving force of ML. Data comes in the form of words and numbers.
Supervised LearningSupervised learning models can accurately predict and classify new data. Supervised learning has a wide range of applications, including classification, regression, and even more complex problems like image recognition and natural language processing. Supervised learning SL is a paradigm in machine learning where input objects for example a vector of predictor variables and a desired output value also known as human labeled supervisory signal train a model The training data is processed building a function that maps new data on expected output values 1