Product-based Recommendation System

This notebook implements a function to generate product recommendations based in TF-IDF and Cosine Similarity

Content

• Requirements: Necessary libraries to run the notebook.
• Data Loading: How to load and prepare data for the recommendation model.
• Model Implementation: Details of the recommendation function implementation.
• Evaluation: Methods to evaluate the accuracy and effectiveness of the model.
• Results: Analysis of the obtained results and visualization of the recommendations.

Usage

To use this notebook, make sure to have the following libraries installed:

pip install pandas numpy scikit-learn

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