Better Software Through Measurement

This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items.
Course info
Rating
(32)
Level
Intermediate
Updated
October 10, 2013
Duration
1h 37m
Table of contents
Instrumentation: Streaming Metrics
Optimizing Conversion: A/B Testing
Recommendations: Item-based Recommendations
Personalized Recommendations: Naive Bayesian Classifier
Finding Groups: k-means Clustering
Description
Course info
Rating
(32)
Level
Intermediate
Updated
October 10, 2013
Duration
1h 37m
Description

This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items. These techniques are at the heart of many of the largest search engines and online retailers, but can be used to good effect for smaller companies. Throughout the course, the emphasis will be on examining and extending working sample code. The algorithms will be presented intuitively and you do not need any advanced math background.

About the author
About the author

Brendan started programming in C on MacOS 7.5 and since then has done everything from embedded systems programming to writing web apps.