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Data Visualization & Communication Exercise
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-118107-EContabilidad y controlDesde 8,20 €
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frog design, Teaching Note
Datar, Srikant M.; Bowler, Caitlin N.Nota del Instructor HBS-119040-EContabilidad y controlTeaching note for 118707.Desde 0,00 €
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Data Science at Target, Teaching Note
Datar, Srikant M.; Bowler, Caitlin N.Nota del Instructor HBS-119108-EContabilidad y controlTeaching note to case 118016Desde 0,00 €
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The Oakland Athletics: Strategy & Metrics for a Budget, Teaching Note
Datar, Srikant M.; Bowler, Caitlin N.Nota del Instructor HBS-119098-ETeaching note for case 118010.Desde 0,00 €
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Data Science at Target
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-118016-EContabilidad y controlParitosh Desai joined Target.com in 2013 as VP of Business Intelligence, Analytics & Testing to explore how the retailer could use its relatively small but thriving e-commerce arm to drive sales and win customers. The case explores the technological and oDesde 8,20 €
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Visualizing Data & Effective Communication
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-118114-EContabilidad y controlDesde 8,20 €
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The Oakland Athletics: Strategy & Metrics for a Budget
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-118010-EDesde 8,20 €
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LendingClub (B): Decision Trees & Random Forests
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-119021-EMarketingThis case builds directly on the case LendingClub (A). In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan. Technical topics include: (1) Decision trees as a modelling technique, overfitting and induction bias, model validation; (2) Random forest as an ensemble-style modelling technique, bootstrapping,...Desde 5,74 €
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Chateau Winery (A): Unsupervised Learning
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-119023-EContabilidad y controlThis case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers' purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups of customers who have purchased any number of 32 specific "deals" Booth offered over the year, differentiated by the wine varietal as well as its country of origin and a minimum num...Desde 8,20 €
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Predicting Purchasing Behavior at PriceMart (A)
Datar, Srikant M.; Bowler, Caitlin N.Caso HBS-119025-EContabilidad y controlThis case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognize retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded a new baby, parents' shopping habits became quickly ingrained. She hypothesized that if she could get households expecting a new baby to make PriceMart a part of their routines befor...Desde 8,20 €