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Predictive Modeling

Predictive modeling is the process of using known results to create, process, and validate a model that can be used to make future predictions. Two of the most widely used predictive modeling techniques are regression and neural networks.
Predictive Modeling

By analyzing historical events, companies can use predictive modeling to increase the probability of forecasting events, customer behavior, as well as financial, economic, and market risks.

The rapid migration to digital products has created a sea of data that is readily available to businesses. Big data is utilized by companies to improve the dynamics of the customer-to-business relationship. This vast amount of real-time data is retrieved from sources such as social media, internet browsing history, cell phone data, and cloud computing platforms.

Predictive modeling is a commonly used statistical technique to predict future behavior. Predictive modeling solutions are a form of data-mining technology that works by analyzing historical and current data and generating a model to help predict future outcomes. In predictive modeling, data is collected, a statistical model is formulated, predictions are made, and the model is validated (or revised) as additional data becomes available.

Probyto AI allows organizations to build and manage such usecases and track the benefits of AI adoption in their businesses. Currently, FREE 60 minutes AI Consultation is being provided to the registered users in the Probyto AI Demo platform. If you haven't registered yet, register now to Probyto AI Demo.

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