Keras is a deep learning library that wraps the efficient numerical libraries Theano and TensorFlow.
In this post, you will discover how to develop and evaluate neural network models using Keras for a regression problem.
After completing this step-by-step tutorial, you will know:
- How to load a CSV dataset and make it available to Keras
- How to create a neural network model with Keras for a regression problem
- How to use scikit-learn with Keras to evaluate models using cross-validation
- How to perform data preparation in order to improve skill with Keras models
- How to tune the network topology of models with KerasKeras is a deep learning library that wraps the efficient numerical libraries Theano and TensorFlow.
In this post, you will discover how to develop and evaluate neural network models using Keras for a regression problem.
After completing this step-by-step tutorial, you will know:
- How to load a CSV dataset and make it available to Keras
- How to create a neural network model with Keras for a regression problem
- How to use scikit-learn with Keras to evaluate models using cross-validation
- How to perform data preparation in order to improve skill with Keras models
- How to tune the network topology of models with Keras
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