BEGIN:VCALENDAR VERSION:2.0 PRODID:-//hacksw/handcal//NONSGML v1.0//EN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20260518T070842Z DESCRIPTION:Click for Latest Location Information: http://edw2019.dataversi ty.net/sessionPop.cfm?confid=126&proposalid=10464\n
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Machi ne Learning (ML) is a form of Artificial Intelligence (AI) that enables com puters to automatically learn and adapt using large volumes of quality data sets. The main goal of ML is to learn from the previous data patterns and make future predictions. Today, ML powers technologies such as facial recog nition, fraud prevention, consumer shopping patterns, equipment failure, an d even self-driving cars. However, the field of ML is vast and complex and this 3-hour tutorial with three basic modules is your entry into the world of ML. This training is designed for analysts, managers, and executives acr oss any industry sector who want to get a broad overview of key ML concepts and techniques . 

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The first module provides an overview of th e basic concepts and building blocks of ML.  This module covers the 5 main types of Analytics and the 3 types of ML. Given that ML heavily involv es techniques from both statistics and computer science, the next two modul es cover these two areas. Module 2 provides an overview of statistical conc epts such as data distributions, sampling, correlation, statistical tests ( such as T-Tests and ANOVA) and more. The third module is on the computer sc ience aspects and covers ML algorithms such as Decision Trees, Support Vect or Machines (SVM), Logistic Regression, Linear Regression, and Clustering. In all the three modules the emphasis is on the ML concepts and their relat ion to the real and enterprise/business world in plain simple English. This is not a ML programming tutorial.

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\n DTSTART:20190317T143000 SUMMARY:Introduction to Machine Learning DTEND:20190317T174459 LOCATION: See Description END:VEVENT END:VCALENDAR