Deep Learning: Recurrent Neural Networks with Python
Master, train, and build recurrent neural networks with Python
Explore the world of Recurrent Neural Networks using Python and learn how to build models that handle sequences of data. You will move from foundational concepts to hands-on projects, including building an automatic book writer and a stock price prediction tool.
Packt | Feb 2021 | 935 min
What You Will Learn
You will start by understanding the core ideas behind recurrent neural networks and their variants. Through a mix of theory and hands-on coding exercises, you will implement RNNs using TensorFlow and apply them to real datasets. By working on practical projects, you will gain confidence in building and deploying your own sequence models.
Key Features
- Build and train RNNs, LSTM, and GRU models for real-world sequence data
- Apply TensorFlow to create, compile, and evaluate recurrent neural networks
- Develop practical projects like text generation and stock price forecasting
Target Audience
This path is ideal for data scientists, analysts, and Python developers who want to add deep learning sequence modeling to their toolkit. If you have a basic understanding of Python and want to learn how to apply RNNs to real problems, you will find the content approachable and directly useful for your work.
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