Articles by Sam Steingold

Sam joined Magnetic in the Fall 2013 and is leading the Data Science team here.

Sam can be found on the web at:

  1. Detecting Brands in User Search Queries

    Capturing user intent with brands can be valuable, especially in online advertising. In the online advertising domain, brand detection can help capture user interests and improve user modeling, which, in turn, can lead to an increase in precision of user targeting with ads relevant to their interests and needs.

  2. Measuring Statistical Lift on Search Categories

    One of the most popular features of the Magnetic Insight platform is our category rankings for an advertiser’s audience of page visitors. The rankings give a completely unbiased look into which search categories are the most popular amongst the users that visit a customer’s different web pages.

    A category lift report from Magnetic Insight

  3. Information Theoretic Metrics for Multi-Class Predictor Evaluation

    How do you decide if a predictive model you have built is any good? How do you compare the performance of two models? As time goes on, data changes and you have to rebuild your models — how do you compare the new model’s behavior on the new data with the old model’s behavior on the old data?

  4. Click Prediction with Vowpal Wabbit

    At the core of our automated campaign optimization algorithms lies a difficult problem: predicting the outcome of an event before it happens. With a good predictor, we can craft algorithms to maximize campaign performance, minimize campaign cost, or balance the two in some way. Without a good predictor, all we can do is hope for the best.