Benjamin Lubin / Materials

SVM Analytics Exercise

This is a case suitable for understanding the role of analytics in finding answers to business questions. Specifically, the case concerns optimizing bids in a Google-style online ad platform.

The exercise is accompanied by a excel spreadsheet which the students use to both perform their SVM-based analytics and seperately to optimizing their bidding strategy.

The case covers:

  • On-line ad auctions

  • Bid optimization & Profit Maximization

  • Analytics, specifically Support Vector Machines (Regression) Usage

The material is appropriate for:

  • MBAs to learn about ad auctions, analytics and to learn about the nature of an example of the kinds of tools involved.

  • An introductory machine learning or analytics class, to introduce the notion of Kernel Machines, and how they can be applied. Further, the spreadsheet is a full (1-D) SVR engine; students can be introduced to the mechanisms of such methods via the spreadsheet content. (If using for this purpose, unhide the rows/columns that define the SVM)

NO software is required other than Excel and the Excel solver. A complete (1-D) Support Vector Regression engine has been coded into the provided Excel spreadsheet.

Asynchronous Workflow Engine

A distributed asynchronous workflow engine, with a complete UI.

Code available on GitHub: workflow engine. Please contact if you are interested in using it (or the accompanying teaching materials) in your class.

APIs via Restaurants

A Class exercise for learning about APIs by building out a restaurant information system.

Code available on GitHub: Restaurant API Exercise. Please contact if you are interested in using it (or the accompanying teaching materials) in your class.

Teaching Dynamic Websites via an Adventure Game

A complete code base (and accompanying materials) for teaching dynamic website creation, by having teams of students create their own choose-their-own adventure game. Our code supports rooms, items, inventory, user actions, and locomotion.

Code available on the public Google SVN server. Please contact if you are interested in using it (or the accompanying teaching materials) in your class.