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.
What you'll learn
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.
Table of contents
- Introduction 1m
- Problem: Discovering Groups 2m
- Demo: Getting A Friend List 1m
- Demo: Sports Teams in Common 2m
- Friend Versus Sports Team Matrix 1m
- Demo: Creating The Friend Matrix 2m
- Overview of k-means Clustering 3m
- Tanimoto Distance 2m
- Demo: Implementing The Tanimoto Distance 3m
- Demo: Implementing k-means 5m
- Summary 2m