- 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
Loading Model for Predictions
To predict the unseen data, you first need to load the trained model into the memory. This is done using the following command −
model = load_model ('./models/handwrittendigitrecognition.h5')
Note that we are simply loading the .h5 file into memory. This sets up the entire neural network in memory along with the weights assigned to each layer.
Now, to do your predictions on unseen data, load the data, let it be one or more items, into the memory. Preprocess the data to meet the input requirements of our model as what you did on your training and test data above. After preprocessing, feed it to your network. The model will output its prediction.
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