Visual Tools for Explaining Machine Learning Models
mer. 8 mai à 23:45
VISUAL TOOLS FOR EXPLAINING MACHINE LEARNING MODELS
Presented by Leonardo Auslender Statistical and data science models are considered to be, somewhat pejoratively, black boxes, because their interpretation has not been systematically studied. Molnar’s “Interpretable Machine Learning” ( https://christophm.github.io/interpretable-ml-book/ ) is a notable effort in finding solutions to this problem. Our presentation is humbler. We will present visual tools for model interpretation based on the partial dependency plot (PDP) and its variants, such as marginal PDPs created by the presenter, some of which may be polemical and debatable. The contents are applicable to a wide variety of models. The presentation is based on a binary target model. WHO SHOULD ATTEND You should know the basics of creating statistical or machine learning models. Some familiarity with partial dependency plots is assumed. You can review this article for background: https://christophm.github.io/interpretable-ml-book/pdp.html ABOUT THE PRESENTER Leonardo is a statistician and economist with 30 years of business experience at Cisco, AT&T Bell Labs, Citibank, SAS Institute, etc., He is an expert and invited speaker in the area of Big Data methods, and the intersection of statistical and data mining models. He has written papers and delivered lectures on Variable Selection, Missing Value Imputation, Tree Regression, Support Vector Machines, Market Basket Analysis, Database Marketing, Customer Relationship Management (CRM), GDP and Relative Price Inflation studies, Expectation Formations, Productivity and Technology effects in the economy. ABOUT YOUR ORGANIZER Principal Analytics Prep is a leading data analytics bootcamp in New York City. We have provided training and career coaching for both STEM and non-STEM people seeking to start new careers in data science and advanced analytics. Our programs offer a small-group, hands-on, collaborative learning environment, supported by a faculty of hiring managers with 10 years+ of practical industry experience. To learn more, visit our website: https://www.principalanalyticsprep.com
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