
Predictive Analytics For Dummies, 2ed
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Predictive Analytics For Dummies, 2e will help the you understand the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. You will learn how to incorporate algorithms through discovering data models, identifying similarities and relationships in your data, and how to predict the future through data classification. You will develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get stakeholder buy-in. The author will also address "soft" issues, including handling people, setting realistic goals, protecting budgets, making useful presentations, and more, to help the reader prepare for shepherding predictive analysis projects through their companies. ·Getting Started with Predictive Analytics ·Incorporating Algorithms in Your Models ·Developing A Roadmap ·Programming Predictive Analytics ·Executing Big Data ·The Part of Tens
Dr. Anasse Bari has over five years of large-scale software architecture experience in designing and implementing software systems under different platforms. He is a Fulbright scholar, a software engineer, and a data mining expert. Dr. Bari works for the World Bank Group in Washington DC. Mohamed Chaouchi has conducted extensive research using predictive analytics and data mining in both the health and financial domains. He holds a patent for a data-mining platform to analyze cancer development. His technical expertise includes service-oriented architecture, web services, and application security. Tommy Jung is a software engineer who has been developing software applications for over 15 years. He has worked extensively on creating analytic's tools for natural language processing in his days at a speech recognition company and then turned his focus to the web analytics, A/B testing, and stock analysis. He has worked at several Fortune 500 companies.