Cryptocurrency Price Prediction for Next 30 Days with Machine Learning

Abstract

The goal of this project is to create a model from machine learning that will predict cryptocurrency prices toward the following 30 days. The main goal is to build a prediction model that is able to predict future swings in prices for selected cryptocurrencies by using historical market data that encompasses price patterns, trading volumes, and appropriate indicators. The key objective of the model is to empower traders and investors functioning in the fluctuating and unpredictable the digital currency market to make well-informed decisions. Throughout every moment of the next 30 days, the model aims to give traders an advantage of strategy in maintaining the cryptocurrency ecosystem through provision of practical information. Key Words: Cryptocurrency, Prediction, LTSM, Normalization, Features Extraction, Pediction Date