I propose the use of recurrent neural networks (RNN) and its variants LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit) for data analysis of the Bitcoin blockchain. These models are key to extracting valuable information and patterns in the cryptocurrency ecosystem.
RNNs, along with their LSTM and GRU variants, are essential for handling large volumes of data from the Bitcoin blockchain and uncovering meaningful trends. These models make it possible to identify suspicious transactions, price fluctuations and other relevant events in the world of cryptocurrencies. Using RNN, LSTM and GRU will open up new opportunities to make informed decisions in this field.