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Models are created using data to make predictions from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Models in data science are built by analyzing data in order to make predictions. The process of creating models begins with collecting relevant data and then using that data to train the model. This training process involves feeding the model with examples of input data and the corresponding correct output. Through this iterative process, the model learns patterns and relationships within the data that can be used to make predictions on new, unseen data. Data is a fundamental component in the creation of models because it serves as the building blocks for training and evaluating the model. The quality, quantity, and relevance of the data used to train the model directly impact the accuracy and effectiveness of the predictions it can make. Therefore, it is crucial for data scientists to carefully s...
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