Cryptocurrency Price Prediction with Recurrent Neural Networks
Author
Shivay Nagpal
Title
Cryptocurrency Price Prediction with Recurrent Neural Networks
Description
Predicting the value of some popular cryptocurrencies using Recurrent Neural Networks
Category
Essays, Posts & Presentations
Keywords
Time-series Forecasting, Recurrent neural network, Deep Learning, Long Short-Term Memory (LSTM), Cryptocurrency Prediction
URL
http://www.notebookarchive.org/2022-01-5l5v84v/
DOI
https://notebookarchive.org/2022-01-5l5v84v
Date Added
2022-01-12
Date Last Modified
2022-01-12
File Size
0.78 megabytes
Supplements
Rights
Redistribution rights reserved
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WOLFRAM INDIA SCHOOL 2022
Cryptocurrency Price Prediction with Recurrent Neural Networks
Cryptocurrency Price Prediction with Recurrent Neural Networks
Shivay Nagpal
St. Stephen's College, University of Delhi
Deep learning is becoming commonplace in many fields of the financial world. The ability to identify and predict patterns in large data sets is a powerful tool which can be deployed in making various kinds of predictions. Since the Cryptocurrency market is considered to be very dynamic and complex in nature, this project aims to use a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) to make short term predictions of the values of various popular cryptocurrencies using the Wolfram Language. The dataset we will use for this project includes market values for three popular cryptocurrencies on the market.
A time series is a sequence of data points of that occur in successive order over some period of time. In this project, we have trained three different Long Short-term Memory (LSTM) Recurrent Neural Networks(RNNs) with historical data of the market values of three popular cryptocurrencies. These neural networks will then be employed to make predictions on the time-series that will then be compared with the real dataset with various statistical parameters.
A time series is a sequence of data points of that occur in successive order over some period of time. In this project, we have trained three different Long Short-term Memory (LSTM) Recurrent Neural Networks(RNNs) with historical data of the market values of three popular cryptocurrencies. These neural networks will then be employed to make predictions on the time-series that will then be compared with the real dataset with various statistical parameters.
Wrangling and exploring the data
Wrangling and exploring the data
Preparing the data for training the neural networks
Preparing the data for training the neural networks
Neural net model trained with one cryptocurrency
Neural net model trained with one cryptocurrency
Alternate neural net model trained with one cryptocurrency
Alternate neural net model trained with one cryptocurrency
Neural net model trained with 3 cryptocurrencies
Neural net model trained with 3 cryptocurrencies
Concluding remarks
Concluding remarks
Keywords
Keywords
Acknowledgment
Acknowledgment
References
References
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Cite this as: Shivay Nagpal, "Cryptocurrency Price Prediction with Recurrent Neural Networks" from the Notebook Archive (2022), https://notebookarchive.org/2022-01-5l5v84v
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