ratings
This course is about the learning process of recommendation systems which offer a way of dealing with the large amount of information and they help users to make the decisions.
Unlimited Duration
January 27, 2021
EXPIRED
Course Description
The goal of an recommendation system over big data is to design a system that is scalable, efficient, and provides the best possible results for a large variety of queries. Most of the existing recommender systems are either based on collaborative c or content based filtering. A recommendation system is an information filtering mechanism that attempts to predict the rating a user would give a particular product.
At the end of course you will learn about the:
- Brief background of spark
-Introduction to ML, AL and DL
-Collaborative collaborative
-Content filtering
Course Curriculum
-
- What is Spark? 00:00:00
- Why Spark? 00:00:00
- Where Spark is used 00:00:00
- A brief background of Spark 00:00:00
- Introduction to Machine Learning, AI & Deep Learning 00:00:00
- Spark ML 00:00:00
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- Introduction to Recommender Systems 00:00:00
- Collaberative Filtering 00:00:00
- Content Filtering 00:00:00
- Machine Learning Workflow 00:00:00
- Recommendation using ALS 00:00:00
- Labs 00:00:00