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A dual-feature data portable MRS designed to predict user's music preferences under two recommending algorithms and bridge the gap between various music streaming platforms, notably Spotify and TIDAL.

Python 95.89% Jupyter Notebook 0.41% CSS 0.02% HTML 0.05% PowerShell 0.01% Shell 0.01% Procfile 0.01% C 1.14% Cython 2.21% C++ 0.12% Fortran 0.02% Smarty 0.01% XSLT 0.01% Makefile 0.01% MATLAB 0.01% TeX 0.06% Roff 0.01% JavaScript 0.03%
collaborative-filtering content-based-filtering data-portability flask recommender-system

music-rs's Introduction

Hi , I am Chen Jin

About Me

  • 🔭 I recently built a self-implementing Operating System with software-level caching I/O, self-implemented malloc and free of which simulates system malloc and free along with security detections of diabolical attacks and undefined behaviors of read and write, concurrent reverse index search engine and concurrent KV storage system.
  • 🌱 I’m currently learning about building and deploying apps using microservices built with Node, React, Docker and Kubernetes
  • 👯 I’m looking to collaborate on fun projects, hackathon, etc.
  • 📫 How to reach me: connect with me on LinkedIn: codeSTACKr | LinkedIn
  • 😄 Pronouns: she/her/hers

Languages and Tools:

Visual Studio Code

HTML5

CSS3

JavaScript

React

Node.js

SQL

MySQL

MongoDB

Git

GitHub

Terminal



image by Chermayeff & Geismar & Haviv

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