This article discusses the categories of machine learning problems, and terminologies used in the field of machine learning. Types of machine learning problems There are various ways to classify machine learning problems. Here, we discuss the most obvious ones. 1. On basis of the nature of the learning “signal” or “feedback” available to a learning system Supervised learning : The computer is presented with example inputs and their desired outputs, given by a “teacher”, and the goal is to learn a general rule that maps inputs to outputs. The training process continues until the model achieves a desired level of accuracy on the training data. Some real life examples are: Image Classification: You train with images/labels. Then in the future you give a new image expecting that the computer will recognize the new object. Market Prediction/Regression: You train the computer with historical market data and ask the computer to predict the ...
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