Predictive Modeling Resources: Machine Learning, Artificial Intelligence, and Data Analytics
Predictive modeling is the area of data analytics concerned with forecasting probabilities and trends. A predictive model is made up of a number of predictors, or variables, that are likely to influence future behavior or results. In marketing, for example, a customer's gender, age, and purchase history might predict the likelihood of a future sale.
Predictive modeling techniques are often iterative involving the collection of data, the formulation of a statistical model, and the approximation of an outcome. The process is refined and validated as more data becomes available. The model may employ a simple linear equation or a complex artificial intelligence algorithm, mapped out by sophisticated software.
Predictive modeling algorithms are used widely in information technology (IT). Applications of predictive modeling include: spam filtering, customer relationship management (CRM), capacity planning, disaster recovery, engineering, meteorology, insurance risk, credit score, and marketing.
If this is your first introduction to predictive modeling, you have come to the right place. Predictive Modeling Resources will help you get started using machine learning techniques quickly and easily.
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