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About the Webinar

Machine Learning (ML) approaches and their supporting technologies can generally be classified as Supervised vs Unsupervised, and within those categories as General or Deep Learning (with Reinforcement Learning as a special case within Supervised Learning). The approaches may be based on biological models or statistical models, or hybrids. As demand for machine learning functionality in consumer and enterprise applications increases, it becomes important to have a framework for comparing ML products and services.

This webinar will present an overview of the machine learning landscape, from platform providers to point solutions in each major ML category, and help participants understand their options for experimentation and deployment of ML-based applications.

About the Speaker

Adrian Bowles

Founder, Storm Insights

Adrian is an industry analyst and recovering academic, providing research and advisory services for buyers, sellers, and investors in emerging technology markets. His coverage areas include cognitive computing, big data / analytics, the Internet of things, and cloud computing. Adrian co-authored Cognitive Computing and Big Data Analytics (Wiley, 2015) and is currently writing a book on the business and societal impact of these emerging technologies. He has held executive positions at several consulting and analyst firms. Adrian also held academic appointments in computer science at Drexel University and SUNY-Binghamton, and adjunct faculty positions in the business schools at NYU and Boston College. He began his career with research and application development roles at IBM and GTE Laboratories. Adrian earned his BA in Psychology and MS in Computer Science from SUNY-Binghamton, and his Ph.D. in Computer Science from Northwestern University.

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