Recommendation System using Python| Association Metrics| Association Rules

This Recommendation System using Python| Association Metrics| Association Rules video would help you guys understand how to generate association rules using python, and how to identify strong association rules using the association metrics. This is part 2 of my session, and for those who would like to refer my part 1 video can use the following link, Part 1: https://youtu.be/EvjY6-pWs_4 The agenda of this session is as follows: 1. A brief recap on part 1 concepts 2. The role of python in data science 3. Introduction to Spyder IDE in Anaconda 4. Data extraction and preparation using python 5. Association rule generation using python – Apriori algorithm 6. Advantages of association rules 7. Challenges in association rules LinkedIn: https://www.linkedin.com/in/ponshankar-palanivel/ Twitter: (@PonshankarP): https://twitter.com/PonshankarP?s=09 Please comment your questions below, and I will try my best to clarify it. #AprioriAlgorithm #ProductRecommendationSystem #AssociationRules #RecommendationSystem #ConsumerDataAnalytics #ConsumerAnalytics #Python #analytics #RetailAnalytics #Algorithms #RealWorldExamples #AdvantagesOfAssociationRules #SpyderIDE #AssociationRuleMining #AdvantagesOfAssociaitonRules #Challenges #FoodRecommendationSystem #ProductRecommenderSystem #ConsumerAnalytics #AssociationMetrics #Pros #PythonInDataScience #DataPreparation #StrongAssociationRule #AssociationRuleLearning #RecommendationSystemUsingAssociationRules