For example, based on the passenger list of the Titanic, it is possible to predict which passengers had a greater chance of surviving the disaster. Example data machine learning This dataset contains input variables and the desired prediction we want to make, namely whether people can survive the disaster. The green columns are the ‘input variables’. Whether they survived is the ‘desired outcome’. Example dataset: Passengers Titanic When your dataset is large enough, you can show the model 70% of your data including the desired outcome.
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We call this the training set. With this, the model you use learns which variables had the greatest influence on the chance of survival. In the table above, on the vertical axis, the green rows are the training set. When you now ‘feed’ Latvia WhatsApp Number List the other 30% of the data set (blue rows) to your model, it can make a prediction based on the input variables. For example, we can find out what the chance of survival is for Rose and Jack. Also read: 12 simple machine learning tools for webshops Supervised Learning We call this way of learning supervised learning .
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This is similar to a baby showing you pictures. If you tell often enough that a picture of a cow is a cow, a baby will eventually recognize this itself. But how do you use supervised learning for marketing campaigns? On the basis of 4 example cases, I will show you how to enrich your dataset with machine learning. In addition to target groups, the results can also provide other valuable insights. The four practical examples that follow cover the following topics: