Book Recommendation System built for Book Lovers📖. Simply Rate ⭐ some books and get immediate recommendations🤩

A compiler for the 🎃 Spooky 😱 programming language 👻

A collection of papers on divergence and quality diversity

推荐算法个人学习笔记以及代码实战

This repository contains collaborative filtering recommender system build in Python with surprise package to predict book ratings in Book-Crossing dataset.

An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀

Get an overview of sneak previews in your local cinema(s)

📱 Trigger easter eggs on mobile device

Client side escape room with mini-tasks leading to a final prize for @muskanrastogi1's birthday.

Project with examples of different recommender systems created with the Surprise framework. Different algorithms (with a collaborative filtering approach) are explored, such as KNN or SVD.

My lib.

Recommendation system for inter-related content. Uses natural language processing and collaborative filtering. Provides recommendations for books, movies, tvshows

A python notebook for building collaborative, content-based, and ml-based recommender systems with Sklearn and Surprise

Farfetch: Understanding the customer

Comparing different recommendation systems algorithms like SVD, SVDpp (Matrix Factorization), KNN Baseline, KNN Basic, KNN Means, KNN ZScore), Baseline, Co Clustering

HAPPY BIRHTDAY TO ME >.<

Repository of OpenClassrooms' AI Engineer path, project #9 : create a books recommandation system, integrate and deploy it as a mobile app

Letters are a timeless classic. Do we really think we’ll one day hold up a record of texts with that same feeling of longing? We help you send your personal letters to your loved ones instantly!

surprise ur crush, friends, family, or lovely person to yourself with this flower 🌸🌹

Where do people look on images in average? At rare, thus surprising things! Let's compute them automatically