Text Prediction Using LSTM

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.

Introduction
Words and sentences
Time series
Import libraries
Download text
Open text file
Print text
Remove numbers
Convert characters to numbers
Total characters
Sequence length
Time series example
Next character example
Vectorization
LSTM