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Cryptocurrency Price Prediction Using Python and ML

M. Sivanagireddy, V. Saiganesh, V. Rakesh, M. Mahesh


 Predicting the price of crypto currencies is one of the popular case research in the information technological know-how community. Over the last two years, geopolitical and economic problems have risen, global currency values have fallen, stock markets have slumped, and investors have lost their wealth. This has created a new interest in digital currencies. Cryptocurrencies, one of the most well-known digital currencies, are in the limelight as investors want some of them and companies are accepting them as payment sources due to stable development in recent years. This project was conducted to predict crypto-currency prices using a machine learning-based neural network with the least model loss at 100 epochs during training. The Technical-Trade-Indicators (TTI) graph shows about 5–10 times actual BTC value in 300 days. This year, we are further supporting this growing confidence among the traders and the changes in the global cryptocurrency chart due to predicted BTC values. The costs of stocks and crypto currencies do not simply depend on the wide variety of those who purchase or sell them. These days, the trade within the costs of these investments also depends on the adjustments within the economic guidelines of the government regarding any cryptocurrency. The feelings of human beings in the direction of a selected crypto foreign money or persona who at once or indirectly suggest a crypto forex additionally result in a massive buying and promoting of a specific crypto forex, ensuing in an alternate in expenses.

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