This repository contains a series of lab exercises designed to explore the fundamentals and advanced concepts of Recommender Systems. Each lab is structured to provide hands-on experience with different recommender algorithms, data preprocessing techniques, and evaluation metrics.
The lab exercises are located in the docs folder. Each lab includes detailed instructions and necessary datasets to complete the exercises.
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Lab 1: fundamental aspects of Pandas DataFrames.
- implementation of the code examples and exercises
- from this website https://realpython.com/pandas-dataframe/#introducing-the-pandas-dataframe
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Lab 2:
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Simple Recommender System using Pandas with movie data analysis, including data import, weighted rating calculations, and basic filtering.
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Lab 3:
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Lab 4:
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Lab 5:
To get started with the labs, clone this repository and navigate to the docs folder where you will find all the lab exercises.