surprise
There are 0 repository under surprise topic.
- Kitabe
Praful932 / Kitabe
Book Recommendation System built for Book Lovers📖. Simply Rate ⭐ some books and get immediate recommendations🤩
Language:HTML 161 - Language:OCaml 150
DanieleGravina / divergence-and-quality-diversity
A collection of papers on divergence and quality diversity
Zu3zz / Person-Recommendation-Algorithms
推荐算法个人学习笔记以及代码实战
Language:Python 51ISG-Siegen / Auto-Surprise
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning :rocket:
Language:Python 26klaudia-nazarko / collaborative-filtering-python
This repository contains collaborative filtering recommender system build in Python with surprise package to predict book ratings in Book-Crossing dataset.
Language:Jupyter Notebook 22Crazy-Marvin / sneak.page
Get an overview of sneak previews in your local cinema(s)
Language:HTML 21WeiChiaChang / easter-eggs-mobile
📱 Trigger easter eggs on mobile device
Language:JavaScript 11akshatvg / Escape-Room
Client side escape room with mini-tasks leading to a final prize for @muskanrastogi1's birthday.
Language:HTML 8ansegura7 / RS_Surprise
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.
Language:HTML 8- Language:JavaScript 8
mohsenMahmoodzadeh / book-crossing-recommender-system
A python notebook for building collaborative, content-based, and ml-based recommender systems with Sklearn and Surprise
Language:Jupyter Notebook 7acdick / touch_driven_recommender_engines
Farfetch: Understanding the customer
Language:Python 6devendrakushwah / recommendation-system-for-inter-related-content
Recommendation system for inter-related content. Uses natural language processing and collaborative filtering. Provides recommendations for books, movies, tvshows
Language:HTML 6fleuryc / OC_AI-Engineer_P9_Books-recommandation-mobile-app
Repository of OpenClassrooms' AI Engineer path, project #9 : create a books recommandation system, integrate and deploy it as a mobile app
Language:Jupyter Notebook 5- VisualAttention-RareFamily
numediart / VisualAttention-RareFamily
Where do people look on images in average? At rare, thus surprising things! Let's compute them automatically
singhsidhukuldeep / Recommendation-System
Comparing different recommendation systems algorithms like SVD, SVDpp (Matrix Factorization), KNN Baseline, KNN Basic, KNN Means, KNN ZScore), Baseline, Co Clustering
Language:Jupyter Notebook 5vrushti-mody / Best-Surprise
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!
Language:CSS 5IssamLL / movies-recommender-system-collaborative-filtering
A recommender system that provides personalized movies recommendations to users based on their preferences and behavior using Collaborative Filtering.
Language:Jupyter Notebook 4- Language:JavaScript 4
khadkarajesh / recommender-system
Implicit Event Based Recommendation Engine for Ecommerce
Language:Python 3noahgift / recommendations
UGC AI: recommendations and sentiment analysis examples using Cloud APIs and more
Language:Jupyter Notebook 3RocioAldanaMendez / FastAPI
EDA development, ETL, API creation, query generation, deploy on two different platforms.
Language:Python 3- YelpRecommender
unclebrod / YelpRecommender
The goal of this project was to build an explicit recommender system using collaborative filtering for restaurants in Charlotte using Yelp's Open Dataset. I wanted to explore the mechanics of recommendations systems, and explore a new library in Surprise.
Language:Jupyter Notebook 3 itsmarmot / hello
surprise ur crush, friends, family, or lovely person to yourself with this flower 🌸🌹
Language:CSS 2JoaoAlfredoAlves / loveSurprise
a little webSiteSurprise for my dear <3 with HTML and CSS
Language:CSS 2shervinee / Amazon_recSys
An Analogous experiment to Netflix Challenege on Amazon DataSet for three popular and efficient approaches
Language:Python 2- Language:HTML 2
Filip-231 / SXI-Tech-Recommender
Recommendation system of possible known technologies for a people with specified tech stack.
Fresh4774 / surprise
This is a surprise i mean something you wont expect so dont judge a book by its home page ;)
Language:CSS 1Krosvick / Pirateca-TIS
PHP MVC Movie Review Web App + recommender system in python
Language:PHP 1leomaurodesenv / databricks-recommendation-system
This is a learning repository about Databricks and Recommendation Systems
Language:Python 1lexxai / goit_python_ds_hw_07
surprise svd
Language:Jupyter Notebook 1Magus4450 / Movie-Recommendation-System-using-Collaborative-Filtering
Collaborative Filtering based movie recommendation that uses matrix factorization to generate rating predictions for user-movie,
Language:Python 1- Language:CSS 1
somuappu75 / Happy-Birthday
A website to wish your loved ones on their Birthday.As a Surprise Gift
Language:CSS 1
