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Introduction to Data Science/ Data Mining for Business ...

BRIAN D ALESSANDRO VP data SCIENCE, DSTILLERY ADJUNCT PROFESSOR, NYU FALL 2014 Introduction to data Science/ data Mining for Business Analytics Fine Print: these slides are, and always will be a work in progress. The material presented herein is original, inspired, or borrowed from others worl. Where possible, attribution and acknowledgement will be made to content s original source. Do not distribute, except for as needed as a pedagogical tool in the subject of data Science. NYU Intro to data Science Copyright: Brian d Alessandro, all rights reserved WHAT IS data SCIENCE? NYU Intro to data Science Copyright: Brian d Alessandro, all rights reserved TOO SEXY FOR THIS COURSE? data scientists are the key to realizing the opportunities presented by big data . They bring structure to it, find compelling patterns in it, and advise executives on the implications for products, processes, and decisions. They find the story buried in the data and communicate it.

Introduction to Data Science/ Data Mining for Business Analytics Fine Print: these slides are, and always will be a work in progress. The material presented herein is original, inspired, or borrowed from others’ worl. Where possible, attribution and

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Introduction to Data Science Data Mining for Business ...

cds.nyu.edu

VP – DATA SCIENCE, DSTILLERY ADJUNCT PROFESSOR, NYU FALL 2014 Introduction to Data Science Data Mining for Business Analytics Fine Print: these slides are, and always will be a work in progress. The material presented herein is original, inspired, or borrowed from others’ worl. Where possible, attribution and

  Business, Introduction, Data, Sciences, Mining, Analytics, Data science, Introduction to data science data, Introduction to data science data mining for business analytics

Covariance matrix - New York University Center for Data ...

cds.nyu.edu

Example 1.9 (Canadian cities). We consider a dataset which contains the locations (latitude and longitude) of major cities in Canada(so d= 2 in this case). Figure1shows a scatterplot of the data. The sample covariance matrix is X = " 524:9 59:8 59:8 53:7 #: (28) The latitudes have much higher variance than the longitudes. Latitude and longitude ...

  Matrix, Major, Cities, Altitude, Covariance, Latitude and longitude, Longitude, Covariance matrix, Major cities

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