Google uses R: a new open-source package for estimating causal effects in time series

In this blog post Google confirms its adoption of the opensource statistical environment R (see my R introduction) releasing a new R package.. “How can we measure the number of additional clicks or sales that an AdWords campaign generated? How can we estimate the impact of a new feature on app downloads? How do we compare the effectiveness of publicity across countries? In principle, all of these questions can be answered through causal inference […] How the package works The CausalImpact R package implements a Bayesian approach to estimating the causal effect of a designed intervention on a time series....

September 16, 2014 · 1 min · 176 words · Matteo Redaelli

Google Predictor API - release 1.2

The Google Predictor API V1.2 is out! “The Prediction API provides pattern-matching and machine learning capabilities. Given a set of data examples to train against, you can create applications that can perform the following tasks: Given a user’s past viewing habits, predict what other movies or products a user might like. Categorize emails as spam or non-spam. Analyze posted comments about your product to determine whether they have a positive or negative tone....

May 19, 2011 · 1 min · 138 words · Matteo Redaelli

Some Reasons for Loving Google Apps

A quick presentation about why people & employees & IT managers & companies should love and adopt Google Apps instead of other old style Intranets (MS Sharepoint, Sap Portal, .. that require the (not user friendly) programmers’s actions checkin/checkout) and Email Suites (MS Exchange)

September 25, 2009 · 1 min · 44 words · Matteo Redaelli