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.

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.

• Instrumentation: Streaming Metrics 19mins
• Optimizing Conversion: A/B Testing 12mins
• Recommendations: Item-based Recommendations 21mins
• Personalized Recommendations: Naive Bayesian Classifier 22mins
• Finding Groups: k-means Clustering 21mins