This hands-on project-based course guides learners through the process of designing, developing, and evaluating a functional Book Recommendation Engine using Python and data science techniques. Beginning with foundational principles, learners will identify key components of recommender systems, prepare structured datasets, and apply user-driven filters to generate personalized recommendations.

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Project on Recommendation Engine - Book Recommender
This course is part of Mastering Recommendation Systems with Python Specialization

Instructor: EDUCBA
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July 2025
7 assignments
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There are 2 modules in this course
This module introduces learners to the core principles of building a book recommendation engine using user-defined filters and structured data. Learners will explore initial project setup, data preprocessing techniques, and the application of foundational filtering logic based on publication metadata and user preferences.
What's included
9 videos4 assignments
This module advances learners into content-based filtering techniques by leveraging text features such as book title, genre, and description. Through the construction of similarity matrices and feature combination strategies, learners will implement a more intelligent and personalized recommendation engine.
What's included
6 videos3 assignments
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Reviewed on Jul 23, 2025
Practical project showcasing recommendation algorithms with clear, book-focused implementation.
Reviewed on Jul 20, 2025
Practical project showcasing book recommendations using real-world data and techniques.
Reviewed on Aug 13, 2025
Practical project showcasing book recommendation engine basics.

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