- Deep Learning with Keras Tutorial
- Deep Learning with Keras - Home
- Deep Learning with Keras - Introduction
- Deep Learning
- Setting up Project
- Importing Libraries
- Creating Deep Learning Model
- Compiling the Model
- Preparing Data
- Training the Model
- Evaluating Model Performance
- Predicting on Test Data
- Saving Model
- Loading Model for Predictions
- Conclusion
- Deep Learning with Keras Resources
- Deep Learning with Keras - Quick Guide
- Deep Learning with Keras - Useful Resources
- Deep Learning with Keras - Discussion
Deep Learning with Keras - Saving Model
We will save the trained model in our local drive in the models folder in our current working directory. To save the model, run the following code −
directory = "./models/"
name = 'handwrittendigitrecognition.h5'
path = os.path.join(save_dir, name)
model.save(path)
print('Saved trained model at %s ' % path)
The output after running the code is shown below −
Now, as you have saved a trained model, you may use it later on for processing your unknown data.
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