roliveira3891 / cryptocurrency-recommender-system

A recommender system that recommends cryptocurrencies to investors.

Cryptocurrency Recommender System

Project Description

A project that utilizes cryptocurrency transaction network and cryptocurrency prices to give personalized recommendations to cryptocurrency investors.

This project consists of a front-end module to show personalized recommendations to investors and two back-end modules to compute recommendations, namely The Recommender System Module and The Trend Prediction Module.

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Back-end Modules Description

1. Recommender System Module

• crawler.py: A crawler library which is capable of crawling address and token transaction data
• address_crawler.py: Calling the crawler module to crawl transaction data by address.
• token_crawler.py: Calling the crawler module to crawl transaction data by token.
• preprocess.py: Prepare address transaction data into the form needed for recommender
• recommend.py: Main recommend function

2. Trend Prediction Module

• price_crawler: Retrieving hourly token price data from CoinGecko
• price_crawler_minute.py: Retrieving archived minute resolution data from Kaggle (https://www.kaggle.com/tencars/392-crypto-currency-pairs-at-minute-resolution)
• trend.py: Hyper-parameter tuning script for hourly data source
• trend_minute.py: Hyper-parameter tuning script for minute resolution data source
• trend_minute_multi_CPU.py: Hyper-parameter tuning script for minute resolution data source, with the support of multi-processing to speed up finetuning process
• backtrader-strategy.ipynb: Backtesting models that we have selected in backtrader and measuring strategies in differentk metrics