recommendations

Sci-Fi worth consuming

A unified, comprehensive and efficient recommendation library

👍👎 A recommendation engine using Likes and Dislikes for your Ruby app

Ten thousand books, six million ratings

Recommendations for secure applications development with Rust

This is a repository of public data sources for Recommender Systems (RS).

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Java-Based Context-aware Recommendation Library

Resources recommended by members of our community. We welcome contributions, so feel free to send us pull requests adding things to the list! The resources in this list automatically get pushed to the http://progdisc.club/resources page.

recommender system tutorial with Python

Larafy is a Laravel package for Spotify API. It is more like a wrapper for the Spotify API.

Telemetry-Aware Addon Recommender

Recommendation engines for developers, easy as π. https://tamber.com

Privacy resources for the layperson. Highlights resources, tools, VPNs, search engines, articles, books, and dark patterns.

📚🐦 Patrick Collison on Twitter: Which five books have influenced you the most? (In terms of shaping your worldview.)

Built-in Movie Graph Example

🐙 Alternative course catalog for Karlsruhe Institute of Technology

Внедрение и эксплуатация PT Application Inspector. Подробнее: https://habr.com/ru/company/pt/blog/557142/

Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.

A UI library for Algolia Recommend, available for Vanilla JavaScript and React.

Market basket recommendations using association rules and apriori

🎥  Simple Python implementation of Funk SVD for MovieLens movie collaborative recommendations.

Dartmouth Course Reviews, Rankings, and Recommendations

Frequent Itemsets via Apriori Algorithm Apriori function to extract frequent itemsets for association rule mining We have a dataset of a mall with 7500 transactions of different customers buying different items from the store. We have to find correlations between the different items in the store. so that we can know if a customer is buying apple, banana and mango. what is the next item, The customer would be interested in buying from the store.

Neo4j Graph Example Movies Recommendation

A self-assessment tool by @CASES-LU to help business owners implement a better cybersecurity strategy.

Design and Implementation of a File Recommendation System Using Collaborative Filtering and Content-Based Recommendation for the Nextcloud Platform

BuiltOn Sneakers Demo Store

Bazaarvoice's Swift SDK