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Textbook in PDF format

This book describes the Artificial Intelligence (AI) tools in concept and how they apply directly to project success. It also demonstrates the strategy and methods used to purchase and implement AI tools for project management. You will understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using Artificial Intelligence for project management improves project success rates. The book features project management success stories and demonstrates how to leave behind that low project success rate for one that is 95 percent or higher. Supplemental teaching materials are available for use as a textbook. Prediction software consists of three components: the input data, software containing the Machine Learning algorithm, and output. The input data typically consists of several characteristics based on historical projects completed by an organization or within an industry. Each project is labeled as “successful” or “not successful.” Success can be user-defined for an organization. The input data was stored in a spreadsheet, but it could have also been stored in a database. The software program was written in Python. The software was hosted in the cloud and used Heroku as an interface for a Web browser. Creating the code for a neural network was fairly straightforward with modern programming utilities