This project was a joint effort by Lucas De Oliveira, Chandrish Ambati, and Anish Mukherjee to create a song and playlist embeddings for recommendations in a distributed fashion using a 1M playlist dataset by Spotify.

Auto Complete / Suggestion feature using Trie data structure

Comprehensive index of entertainment resources.

Trying to learn some web scraping. This tool is the first mini project I've made.

This Recommendation system will use your playlist and your friend’s playlist and combine them to make the perfect curated playlist consisting of songs that cater to the tastes of both you and your friend.

Auto Complete / Suggestion feature using Trie data structure

Terminology metadata recommendations by TIB

A Movie Recommendation System using Collaborative Filtering Techniques

Displays Algolia product recommendations on PDP and Shopping Cart pages

메뉴 결정 도우미!

This repository analyze user interactions with articles on the IBM Watson Studio platform and develop recommendation systems to suggest new articles that align with their interests.

using serializd.com data to train my LLM model on my taste in television content. feeding reviews, watched shows, and using tmdb api to fetch more details to give a clear analysis. will replicate the same for letterboxd.

Content Based Recommendation System. This is a video recommendation system that uses the input variables Like,Share,Download,Bookmark,Comment to recommend a video

This project focuses on how pricing of AirBnB houses differ according to neighborhoods. It also looks on how important the description of the house is and how a customer is swayed by it. The Data set has been taken from Kaggle.

Music recommendation based on ChatBot with the help of user emotions

Official Website of https://github.com/tamlhp/awesome-recsys-poisoning

Recommendation model of articles on IBM Watson Studio Platform

Team - Brogrammers. Ideathon 2018. Won 2nd Prize