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Utils - Keras Documentation

https://keras.io/utils/

CustomObjectScope keras.utils.CustomObjectScope() Provides a scope that changes to _GLOBAL_CUSTOM_OBJECTS cannot escape.. Code within a with statement will be able to access custom objects by name. Changes to global custom objects persist within the enclosing with statement. At end of the with statement, global custom objects are reverted to state at beginning of the with statement.

tf.keras.wrappers.scikit_learn.KerasRegressor | TensorFlow ...

https://www.tensorflow.org/api_docs/python/tf/keras/wrappers/scikit_learn/KerasRegressor

Pre-trained models and datasets built by Google and the community

tensorflow - 'KerasRegressor' object has no attribute 'to ...

https://stackoverflow.com/questions/44345410/kerasregressor-object-has-no-attribute-to-json

You first need to access the under lying model over which the kerasregressor wrapper is used, and then call save on it. Use model.model.tojson() and model.model.save_weights() – Vivek Kumar Jun 4 '17 at 1:55

Epoch is not working properly for KerasRegressor · Issue ...

https://github.com/keras-team/keras/issues/6521

I'm just getting start with Keras using tensorflow, In the code code I have specified nb_epoch=100 but it's not running for 100 epoch, instead it's executing only for 10 epoch. I wonder is there any bug in my code. Also attaching the out...

Use Keras Deep Learning Models with Scikit-Learn in Python

https://machinelearningmastery.com/use-keras-deep-learning-models-scikit-learn-python/

Keras is one of the most popular deep learning libraries in Python for research and development because of its simplicity and ease of use. The scikit-learn library is the most popular library for general machine learning in Python.. In this post you will discover how you can use deep learning models from Keras with the scikit-learn library in Python.

Plotting Learning Curves — scikit-learn 0.21.2 documentation

https://scikit-learn.org/stable/auto_examples/model_selection/plot_learning_curve.html

On the left side the learning curve of a naive Bayes classifier is shown for the digits dataset. Note that the training score and the cross-validation score are both not very good at the end. However, the shape of the curve can be found in more complex datasets very often: the training score is very ...

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