In this video, Shreya Modak, a DSP Student of Imarticus Learning, explains the two aspects of Artificial Intelligence – Supervised and Unsupervised learning, with examples. She explains that supervised learning is the most common data type of Machine Learning that is further divided into regression or classification. Regression defines the relationship variables, in which one is an input variable and one is a response variable.
Regression has two or more variables – dependent and independent. In classification, we have a dependent variable and the outcome will be either a yes or no. Shreya also elaborates that in unsupervised learning, there is no target variable. There are input variable and training data set.
It is used for finding patterns and structures in the data. She describes unsupervised learning with a detailed example of K-means clustering, which is the most widely used algorithm and one of its key platforms is Facebook. Check our complete #ImarticusPrograms playlist here: http://bit.ly/2JP52hM Subscribe to our channel to get video updates. Hit the subscribe button above. – – – – – – – – – – – – – – – – –
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