Titlebook: Applied Recommender Systems with Python; Build Recommender Sy Akshay Kulkarni,Adarsha Shivananda,V Adithya Krish Book 2023 Akshay Kulkarni,

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Collaborative Filtering Using Matrix Factorization, Singular Value Decomposition, and Co-ClusteringThe basic arithmetic method of calculating cosine similarity to find similar users falls into the memory-based approach. Each approach has pros and cons; depending on the use case, you must select the suitable approach.

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Akshay Kulkarni,Adarsha Shivananda,V Adithya KrishCovers hybrid recommender systems, deep learning-based techniques, and graph-based recommender systems.Includes step-by-step implementation of all techniques using Python with real-world examples.Expl

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Literatures, Cultures, and the EnvironmentMarket basket analysis (MBA) is a technique used in data mining by retail companies to increase sales by better understanding customer buying patterns. It involves analyzing large datasets, such as customer purchase history, to uncover item groupings and products that are likely to be frequently purchased together.

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https://doi.org/10.1007/978-3-030-82102-9The previous chapters implemented recommendation engines using content-based and collaborative-based filtering methods. Each method has its pros and cons. Collaborative filtering suffers from cold-start, which means when there is a new customer or item in the data, recommendation won’t be possible.

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https://doi.org/10.1007/978-4-431-55921-4A classification algorithm-based recommender system is also known as the .. The goal here is to predict the propensity of customers to buy a product using historical behavior and purchases.

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