python-kerasHow do I save a Keras model in Python?
Saving a Keras model in Python is relatively simple and can be done in a few lines of code. To save a model, we use the model.save()
function. This function takes in a file path to save the model to. For example:
model.save('model.h5')
This will save the model as an HDF5 file called model.h5
.
The model.save()
function has several optional parameters that can be used to customize the saving process. For example, the include_optimizer
parameter can be set to True
to save the state of the optimizer used to train the model, allowing the model to resume training where it left off.
The following is a list of the parts of the code and a brief explanation of each:
model.save()
: This is the function used to save the model.model.h5
: This is the file path to save the model to.include_optimizer
: This is an optional parameter that can be set toTrue
to save the state of the optimizer used to train the model.
For more information on saving Keras models, please see the Keras documentation.
More of Python Keras
- How do I use Python Keras to zip a file?
- How can I use XGBoost, Python and Keras together to build a machine learning model?
- How can I use YOLO with Python and Keras?
- How can I use word2vec and Keras to develop a machine learning model in Python?
- How can I use Python and Keras to forecast time series data?
- How can I install the python module tensorflow.keras in R?
- How do I use Python Keras to create a Zoom application?
- How do I use a webcam with Python and Keras?
- How can I improve the validation accuracy of my Keras model using Python?
- How do I use validation_data when creating a Keras model in Python?
See more codes...