Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliographic Details
Main Authors:	Zaman, Md. Sayeed Ibne, Kamal, Mir Ishraq, Ishan, Samiu Mostafa, Khan, Shafayat Zamil, Hossain, Samiha
Other Authors:	Esfar-E-Alam
Format:	Thesis
Language:	English
Published:	Brac University 2022
Subjects:	Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency
Online Access:	http://hdl.handle.net/10361/17208

id	10361-17208
record_format	dspace
spelling	10361-172082022-09-13T21:01:40Z Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping Zaman, Md. Sayeed Ibne Kamal, Mir Ishraq Ishan, Samiu Mostafa Khan, Shafayat Zamil Hossain, Samiha Esfar-E-Alam Department of Computer Science and Engineering, Brac University Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 36-37). Cryptocurrency has been a fascinating topic of many over the past few years, as many people are starting to trade these currencies for big cash-outs. It is a decentralized digital currency. It is a cryptocurrency that has used cryptography to manage the trading systems, creation, and management without relying on any third parties. Since the innovation of the first cryptocurrency Bitcoin in 2009, its value has skyrocketed. Starting from 0.09to42, 226 per bitcoin, it’s a very big market. New services, new companies are accepting it as it seems to be the new future. It is an encrypted peer-to-peer network for simplifying digital exchange. Blockchain-based currency has been the topic of many discussions and is widely popular lately. We decided to analyze the predictability of currency prices by using a machine learning algorithm widely known as the LSTM method. LSTM (Long Short-Term Memory) is a module provided for RNN, later developed and popularized by many researchers; like RNN, the LSTM also consists of modules with recurrent consistency and it works well with short time-sequential datasets. LSTM networks are well-suited for processing and making predictions. This machine-learning algorithm was developed to deal with vanishing gradient points encountered when training traditional RNNs and predict multiple currency prices for a short time interval. It will help traders and buyers to understand more about the price volatility of cryptocurrencies at one-minute intervals for real-life buy and sell. Md. Sayeed Ibne Zaman Mir Ishraq Kamal Samiu Mostafa Ishan Shafayat Zamil Khan Samiha Hossain B. Computer Science and Engineering 2022-09-13T06:39:20Z 2022-09-13T06:39:20Z 2021 2021-01 Thesis ID 21141073 ID 17101459 ID 18101452 ID 17101277 ID 17301185 http://hdl.handle.net/10361/17208 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 37 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency
spellingShingle	Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency Zaman, Md. Sayeed Ibne Kamal, Mir Ishraq Ishan, Samiu Mostafa Khan, Shafayat Zamil Hossain, Samiha Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Esfar-E-Alam
author_facet	Esfar-E-Alam Zaman, Md. Sayeed Ibne Kamal, Mir Ishraq Ishan, Samiu Mostafa Khan, Shafayat Zamil Hossain, Samiha
format	Thesis
author	Zaman, Md. Sayeed Ibne Kamal, Mir Ishraq Ishan, Samiu Mostafa Khan, Shafayat Zamil Hossain, Samiha
author_sort	Zaman, Md. Sayeed Ibne
title	Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
title_short	Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
title_full	Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
title_fullStr	Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
title_full_unstemmed	Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
title_sort	cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/17208
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_version_	1814306931350700032

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping

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