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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.
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Course Access
Unlimited Duration
Last Updated
July 30, 2021
Students Enrolled
20
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Certification
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
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- 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
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