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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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Unlimited Duration

Last Updated

July 30, 2021

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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
    • 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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