Introduction to Supervised Machine Learning

Supervised learning provides you with a powerful tool to classify and process data using machine language. With supervised learning you use labeled data, which is a data set that has been classified, to infer a learning algorithm. The data set is used as the basis for predicting the classification of other unlabeled data through the use of machine learning algorithms. In Chapter 5, we will be covering two important techniques in supervised learning:
▪Linear Regression, and
▪Classification Techniques.
Linear Regression:
Linear regression is a supervised learning technique typically used in predicting, forecasting, and finding relationships between quantitative data. It is one of the earliest learning techniques, which is still widely used. For example, this technique can be applied to examine if there was a relationship between a company’s advertising budget and its sales. You could also use it to determine if there is a linear relationship between a particular radiation therapy and tumor sizes.

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