Book Recommendation Systems

This repository includes approaches to clean, transform and run recommendation algorithms on the Book Crossing data set. We followed some of the data cleaning approaches found here.

Algorithms used:

Name		Name	Last commit message	Last commit date
Latest commit History 55 Commits
.idea		.idea
.ipynb_checkpoints		.ipynb_checkpoints
data		data
deprecated		deprecated
.gitignore		.gitignore
Machine Learning Project - Matrix Factorization.ipynb		Machine Learning Project - Matrix Factorization.ipynb
Machine Learning Project - SVD Method.ipynb		Machine Learning Project - SVD Method.ipynb
Machine Learning Project - UB and IB Methods.ipynb		Machine Learning Project - UB and IB Methods.ipynb
Machine Learning Project - kNN - KNeighbors - Supervised.ipynb		Machine Learning Project - kNN - KNeighbors - Supervised.ipynb
Machine Learning Project - kNN - NearestNeighbours - Unsupervised.ipynb		Machine Learning Project - kNN - NearestNeighbours - Unsupervised.ipynb
Machine Learning Project-Learning to Rank Extra with optimization and book features.ipynb		Machine Learning Project-Learning to Rank Extra with optimization and book features.ipynb
Machine Learning Project-Learning to Rank Stock.ipynb		Machine Learning Project-Learning to Rank Stock.ipynb
Machine Learning Project-Making Necessary Files.ipynb		Machine Learning Project-Making Necessary Files.ipynb
Merge and unifying isbn.ipynb		Merge and unifying isbn.ipynb
Presentation.pptx		Presentation.pptx
README.md		README.md
books_retrieved_0_through_961.csv		books_retrieved_0_through_961.csv
data.py		data.py
data_clean.ipynb		data_clean.ipynb
multiple_isbn_dict.pickle		multiple_isbn_dict.pickle

GoldbergData/Machine-Learning-Book-Ratings

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Book Recommendation Systems

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