Cryptocurrency Price Prediction with LSTM Neural Networks: Capturing market volatility for better forecasting

Cryptocurrencies have gained significant popularity in recent years, with Bitcoin being the most well-known and widely traded cryptocurrency. As the cryptocurrency market continues to evolve, investors and traders are constantly seeking ways to predict price movements and make informed decisions.

In this tutorial, we will explore how to use LSTM (Long Short-Term Memory) neural networks to predict cryptocurrency prices. LSTM networks are a type of recurrent neural network (RNN) that are particularly effective in capturing long-term dependencies in time series data. We will leverage the power of LSTM networks to capture the market volatility and improve our price forecasting accuracy.

Photo by Jack B on Unsplash

Table of Contents

1. Understanding LSTM Neural Networks
2. Data Collection
3. Data Preprocessing
4. Building the LSTM Model
5. Training the LSTM Model
6. Evaluating the Model
7. Making Predictions
8. Conclusion

Understanding LSTM Neural Networks