Abstract: "Machine Learning Cryptocurrency Prediction for Bitcoin and Ethereum" aims to develop a predictive model using historical data to predict the future prices of Bitcoin and Ethereum. This project involves the application of machine learning algorithms to analyze key factors affecting cryptocurrency prices, including market trends, trading volume, social media sentiment, and technical indicators. Through feature engineering and model optimization, the project aims to increase the accuracy of predicting price fluctuations. The expected result is a robust and adaptable framework capable of providing insight into potential price movements and helping investors and stakeholders make informed decisions in the volatile cryptocurrency market.
Keywords: Machine Learning, Time Series Analysis, Sentiment Analysis, Regression Analysis, Deep Learning and more.
Cite:
Prof. Pravin M. Tambe, Siddhi D. Rasal, Pooja A. Sangle, Kaveri B. Gorane, "Review on: Machine Learning Cryptocurrency Price Prediction", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 1, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13106.
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DOI:
10.17148/IJARCCE.2024.13106
