Learn how to implement text prediction using Long Short-Term Memory (LSTM) networks in this 29-minute tutorial. Explore the power of LSTMs for timeseries forecasting and sequence predictions, with a focus on natural language processing. Dive into the process of training an LSTM network on English text and predicting letters based on the training data. Follow along as the tutorial covers importing libraries, downloading and preprocessing text data, converting characters to numbers, and understanding key concepts like sequence length and vectorization. Gain practical insights into applying LSTM to time series and next character prediction examples. Access the code demonstrated in the video through the provided GitHub repository for hands-on practice and further exploration.