Top 10 Predictive Analytics experts to follow

Dr. Eric Siegel – A renowned of “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die,” Siegel is a leading figure in the field. He's the founder of the Predictive Analytics series and a former computer science professor at Columbia University.

Dr. Dean Abbott – As the Co-Founder and Data Scientist of SmarterHQ, Abbott's contributions to data preparation, visualization, and advanced modeling techniques have been pivotal. He's the author of “Applied Predictive Analytics” and frequently speaks at analytics conferences.

Dr. Hilary Mason – A data scientist and entrepreneur, Mason was the Chief Scientist at Bitly and co-founded Fast Forward Labs, a learning research company. Her insights into the practical applications of predictive analytics invaluable.

Nate Silver – Known for his accurate political forecasting and the founder of FiveThirtyEight, Silver leverages predictive analytics in the realm of politics, sports, and more, emphasizing the importance of both statistical and subjective components.

Dr. Kira Radinsky – Radinsky has made headlines for her work in developing a software capable of predicting events, from disease outbreaks to political riots, by analyzing news articles and historical data.

Bernard Marr – An internationally , keynote speaker, and futurist, Marr's work often delves into the practical applications of predictive analytics in various business contexts. His books, such as “Data Strategy”, are crucial reads for anyone interested in data-driven decision making.

Dr. Usama Fayyad – A data mining and data science pioneer, Fayyad was Microsoft's first-ever Chief Data Officer and holds over 30 patents. His insights into the of predictive analytics and its implications are indispensable.

Dr. Vincent Granville – With a background spanning from post-doctoral work in statistical genetics to being a Senior Data Scientist at Visa, Granville co-founded Data Science Central, a resource hub and community for data practitioners.

Dr. John Elder – Founder of Elder Research, a top data science consultancy firm, Elder's expertise in data mining and predictive analytics has been tapped by various , from government agencies to Fortune 500 companies.

Dr. Andrew Ng – While Ng is broadly recognized for his work in machine learning and co-founding Google Brain, his teachings and research often intersect with predictive analytics. As a Stanford professor and co-founder of Coursera, he's made advanced analytics accessible to a global audience.

Top 10 Predictive Analytics experts to follow

Dr. Eric Siegel: of the Predictive Analytics World conference series, Siegel is a recognized figure in the field. His , “Predictive Analytics,” has been influential in providing a guide to the subject.

Dr. Dean Abbott: Co-founder of SmarterHQ, Abbott has over three decades of in data mining and predictive analytics. His contributions lie in the development of anomaly detection algorithms and time series forecasting.

Prof. Usama Fayyad: As a former Data Officer of Yahoo! and a veteran in the data analytics space, Fayyad's insights into large-scale data strategy and predictive modeling have shaped industries.

Dr. Kira Radinsky: Radinsky is the Chairwoman & CTO of Diagnostic , where predictive analytics plays a central role. Known for her work on predicting global events using large-scale data, she was cited in the “30 Under 30” list by Forbes.

Prof. Robert Nisbet: A leading educator in the domain, Nisbet's writings, particularly the “Handbook of Statistical Analysis & Data Mining Applications,” are considered foundational texts in predictive analytics.

Dr. John Elder: Founder of Elder , a data science consultancy, Elder's work on data mining and investment strategies demonstrates the -world impact of predictive analytics.

Dr. Hilary Mason: The founder of Fast Forward Labs (now Cloudera Fast Forward), Mason's expertise lies in the practical implications and applications of big data and predictive modeling in diverse sectors.

Prof. Nathaniel Dean: As a researcher at Texas State University, Dean's work focuses on network structures, algorithms, and their implications for predictive analytics.

Dr. Bernard Marr: A bestselling author and speaker, Marr's insights into big data, artificial intelligence, and analytics have made him a sought-after expert on how predictive analytics is transforming businesses.

Prof. Trevor Hastie: Based at Stanford University, Hastie's contributions, particularly his book “The Elements of Statistical Learning,” are seminal in the domain of statistical modeling and applications in prediction.

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