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Predicting Cryptocurrency Prices

About

This is our Mini-Project for SC1015 (Introduction to Data Science and Artificial Intelligence) which aims to predict cryptocurrency prices of popular cryptocurrencies, scraping data from Yahoo-Finance

Contributors

  • @NotAnAddictz - Data Extraction, Tensorflow, FbProphet
  • @weix1233 - FbProphet, Tensorflow
  • @avdheshcharjan - Data Visualisation, Data Extraction, FbProphet

Main Packages Used

  • pandas_datareader
  • fbprophet
  • matplotlib
  • tensorflow
  • seaborn
  • sklearn

Datasets Used (Scraped from Yahoo Finances)

  • AAVE (AAVE)
  • BinanceCoin (BNB)
  • Bitcoin (BTC)
  • ChainLink (LINK)
  • Cardano (ADA)
  • Ethereum (ETH)
  • Solana (SOL)
  • Tether (USDT)
  • Uniswap (UNI1)

Defining the Problem

  • Are we able to accurately predict the future prices of the various cryptocurrencies?
  • Which machine-learning model is more accurate in their prediction?

Models Used

  • Tensorflow LSTM
  • FbProphet

Conclusion

  • Changes in cryptocurrency prices are not reliant on other cryptocurrencies
  • Cryptocurrencies are generally predictable as long as there is no sudden changes that affects their prices significantly
  • Future prediction will have a wider range the further one predicts
  • Having a larger (and more recent) dataset will result in higher prediction accuracy
  • FbProphet seems to be clearer and more accurate in predicting various cryptocurrencies

What did we learn

  • Scraping datasets using pandas datareader
  • FbProphet and its implementation
  • Neural Networks, Keras and Tensorflow
  • Data Visualisation

References