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Answering the question “how much” with a continuous target variable (number).If you want to go deeper, you should invest a little bit more time in that by reading some books about it, taking an online course or sneaking into a Machine Learning university class.Īnyway, as you’ve read in Part 1, there are two common cases in Predictive Analytics. These differ mostly in the math behind them, so I’m going to highlight here only two of those to explain how the prediction itself works. It’s an iterative task and you need to optimize your prediction model over and over. And there is never one exact or best solution. It needs as much experience as creativity. Creating the right model with the right predictors will take most of your time and energy. This is the heart of Predictive Analytics. Let’s continue with: Step 4 – Pick the right prediction model and the right input values! We reviewed different types of target variables, the overfitting issue, and the question of data splitting (training and test set).Īt the end of this article, you will have a great overview of how Predictive Analytics works in real life! And don’t worry, this is still a 101 article you will understand this one without a PhD in mathematics too. In Part 1 I introduced the main concept of Predictive Analytics and also wrote about how predictions are useful for all online businesses. If you haven’t read Part 1, please do that here: Predictive Analytics 101 Part 1. Last week I promised to continue with the second Part of Predictive Analytics 101.