Machine Learning & Algorithms

Introduction to Machine Learning

So far in the book, we have had an analyst at the heart of the data analysis. In a perfect environment, the analyst may go through the following steps:
  1. Step 1. Analyze data on a certain business problem. Let us say that the analyst is trying to predict which insurance customers will make a claim. The analyst will usually start with past data to see – perhaps through a variant of regression analysis – whether the chance of a customer making a claim can be explained using existing data.
  2. Step 2. Build a model for business predictions and decisions in the area. The analyst may use the analysis in Step 1 to build a predictive model that can be used to predict claims, based ...

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