Lecture
Creating an LSTM Model for Next Character Prediction
In this lesson, we will directly build a simple LSTM model using TensorFlow and Keras.
The practice code is an example of using an LSTM model to predict the next character from a given string.
The training data consists of the string "hello rnn world", and the machine learning model takes a sequence of 3 characters as input to predict the next single character.
For example, when given the input "hel", the model predicts the next character "l".
Lessons in this chapter · Introduction to RNN (Recurrent Neural Networks)
- 1. RNN: Neural Networks That Remember Sequences
- 2. Structure and Principles of RNNs
- 3. What Is the Long-Term Dependency Problem?
- 4. Multiple Choice Quiz
- 5. LSTM: Remembering Long-Term Information
- 6. GRU: A Simpler Recurrent Neural Network
- 7. Transformer: Processing Sentences All at Once
- 8. Building an LSTM Model to Predict the Next Character
- 9. Fill-in-the-Blank Quiz
Lecture
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