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.
Introduction and installation of Apache Spark - Python Tutorial
From the course: Building Recommender Systems with Machine Learning and AI
Introduction and installation of Apache Spark
- So far, we've been using the 100,000 ratings dataset from MovieLens as we illustrate different recommender systems. That's good enough for educational purposes, but if you want to build a recommender system for a real company, you will probably be working with much more data and you certainly won't be processing it just on your own desktop PC. This next section is about scaling it up, systems that exist to train recommender systems with real big data on a cluster, maybe even in the cloud. There are lots of options, but we'll cover a few of my favorites here. So far, we've been using the 100,000 ratings dataset from MovieLens as we illustrate different recommender systems. That's good enough for educational purposes, but if you want to build a recommender system for a real company, you will probably be working with much more data and you certainly won't be processing it just on your own desktop PC. This next section is about scaling it up, systems that exist to let you train…
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)
Introduction and installation of Apache Spark5m 49s
-
(Locked)
Apache Spark architecture5m 13s
-
(Locked)
Movie recommendations with Spark, matrix factorization, and ALS6m 2s
-
(Locked)
Recommendations from 20 million ratings with Spark4m 57s
-
(Locked)
Amazon DSSTNE4m 41s
-
DSSTNE in action9m 25s
-
(Locked)
Scaling up DSSTNE2m 14s
-
(Locked)
AWS SageMaker and factorization machines4m 24s
-
(Locked)
SageMaker in action: Factorization machines on one million ratings, in the cloud7m 39s
-
(Locked)
-
-
-
-