From the course: Building Recommender Systems with Machine Learning and AI
Unlock this course with a free trial
Join today to access over 23,200 courses taught by industry experts.
Implement a stoplist - Python Tutorial
From the course: Building Recommender Systems with Machine Learning and AI
Implement a stoplist
- [Instructor] Given how important a good stoplist is in the real world, it's worth your time to actually go and implement one. So that's your next exercise. Try modifying our RBM example from earlier in the course, to filter out any movies that contain words on a stoplist from the training stage entirely. Your goal is to make sure that our recommender system doesn't even know these titles exist. To do so, you'll have to modify the RBM algorithm class to apply this stoplist, as it's building up the training matrix. That's probably the only hint you need. Give it a go, and when we come back, I'll show you how I did it.
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
-
-
-
-
-
-
-
-
-
(Locked)
The cold start problem (and solutions)6m 12s
-
(Locked)
Implement random exploration54s
-
(Locked)
Exercise solution: Random exploration2m 18s
-
(Locked)
Stoplists4m 48s
-
(Locked)
Implement a stoplist32s
-
(Locked)
Exercise solution: Implement a stoplist2m 22s
-
(Locked)
Filter bubbles, trust, and outliers5m 39s
-
(Locked)
Identify and eliminate outlier users44s
-
(Locked)
Exercise solution: Outlier removal4m
-
Fraud, the perils of clickstream, and international concerns4m 33s
-
(Locked)
Temporal effects and value-aware recommendations3m 30s
-
(Locked)
-
-
-