This project uses a Long Short-Term Memory (LSTM) network implemented with TensorFlow to generate Powerball lottery numbers. The LSTM is a type of Recurrent Neural Network (RNN) that can learn and predict based on long-term dependencies, which theoretically makes it suitable for time series prediction.

This model is purely experimental and is not intended to, nor does it offer a reliable or accurate method for predicting Powerball numbers. The Powerball lottery's outcome is determined by a random process that cannot be accurately predicted by this or any other statistical method. Any use of this model is at your own risk, and it should not be used as a basis for participating in any form of gambling.

Load your data from a .csv file named "powerball.csv". Run the Python script to train the LSTM model on your data. The model will print predicted Powerball numbers.

Any contributions to this experimental project are welcome. Potential future improvements could include testing other models or preprocessing methods, or exploring different ways of handling out-of-range and duplicate predictions.