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Market Basket Analysis in Python

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

What do Amazon's product recommendations and Netflix movie recommendations have in common? Both use Market Basket Analysis, which is a powerful tool that transforms large amounts customer transaction data and viewing data into simple rules for recommending products. This course will show you how to perform Market Basket Analysis using the Apriori algorithm, standard and custom metrics, association rules, and pruning. Interactive exercises will allow you to strengthen your skills and make recommendations for small grocery stores and libraries, ebook sellers, novelty gift shops, and movie streaming service providers. Hidden insights will help you make better recommendations to your customers.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Data Manipulation with pandas

What You Will Learn

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations

In this course, you’ll learn how to perform Market Basket Analysis using the Apriori algorithm, standard and custom metrics, association rules, aggregation and pruning, and visualization

You’ll then reinforce your new skills through interactive exercises, building recommendations for a small grocery store, a library, an e-book seller, a novelty gift retailer, and a movie streaming service

Course Instructors

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Isaiah Hull

Economist

Isaiah Hull is a senior economist in the research division at Sweden's Central Bank (Sveriges Riksbank) and the author of Machine Learning for Economics and Finance in TensorFlow 2. He holds a PhD in...
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