HBSP (USA)
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Philips' Connected Baby Bottle
Lal, Rajiv; Datar, Srikant M.; Bowler, Caitlin N.Case HBS-519020-EMarketingStarting at €8.20
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Herborist
Deighton, John; Kornfeld, Leora; He, Yanqun; Jiang, QingyunCase HBS-511051-EMarketingGlobal brands such as L'Oreal and Oil of Olay dominate China's skin care market. A Chinese domestic brand, after some success in partnership with Sephora in Europe, aspires to challenge the French and U.S. brands' hold on the China market. It must decide how to segment the market, how to position against global assurances of quality and purity, and how to balance its Chinese heritage claims with claims of modernity. The China skin care market is ...Starting at €8.20
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LendingClub (C): Gradient Boosting & Payoff Matrix
Datar, Srikant M.; Bowler, Caitlin N.Case HBS-119022-EMarketingThis case builds directly on the cases LendingClub (A) and (B). In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default on his loan. Having now built three models, Figel compares them to determine which model is most effective at classifying borrowers correctly then uses that model to determine how t...Starting at €5.74
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LendingClub (A): Data Analytic Thinking (Abridged)
Datar, Srikant M.; Bowler, Caitlin N.Case HBS-119020-EMarketingLendingClub was founded in 2006 as an alternative, peer-to-eer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns grades and sub-grades to each application using its own risk evaluation model, it also makes detailed data on each loan applications available to both kinds of investors for their own...Starting at €8.20
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LendingClub (B): Decision Trees & Random Forests
Datar, Srikant M.; Bowler, Caitlin N.Case 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,...Starting at €5.74