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Saving model architecture only
<!DOCTYPE html>Saving model architecture only Saving model architecture only¶In this reading you will learn how to save a model's architecture, but not its weights.In [1]: import tensorflow as tffrom tensorf...…
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Saving and loading models
<!DOCTYPE html>Week 4 Programming Assignment Programming Assignment¶Saving and loading models, with application to the EuroSat dataset¶Instructions¶In this notebook, you will create a neural network that c...…
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Saving and loading model weights
<!DOCTYPE html>Coding Tutorial In [3]: import tensorflow as tfprint(tf.__version__) 2.0.0Saving and loading models¶Coding tutorials¶1. Saving and loading model weights¶2. Model saving criter...…
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Explanation of saved files
<!DOCTYPE html>Explanation of saved files Explanation of saved files¶In this reading, we'll take a closer look at the files saved by the ModelCheckpoint callback, when saving weights only.Previously, you experimente...…
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Validation, regularization, callbacks
<!DOCTYPE html>Coding Tutorial In [45]: import tensorflow as tfprint(tf.__version__) 2.0.0Validation, regularisation and callbacks¶Coding tutorials¶1. Validation sets¶2. Model regularisation...…
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The logs dictionary
<!DOCTYPE html>Logs dictionary Using the logs dictionary¶In this reading, we will learn how to take advantage of the logs dictionary in Keras to define our own callbacks and check the progress of a model.In [1]...…
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Model validation on the Iris dataset
<!DOCTYPE html>Week 3 Programming Assignment Programming Assignment¶Model validation on the Iris dataset¶Instructions¶In this notebook, you will build, compile and fit a neural network model to the Iris da...…
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Batch normalization
<!DOCTYPE html>Batch normalisation Batch normalisation layers¶In this reading we will look at incorporating batch normalisation into our models and look at an example of how we do this in practice.As usual, let's fi...…
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Additional callbacks
<!DOCTYPE html>Additional callbacks Additional callbacks¶In this reading we'll be looking at more of the inbuilt callbacks available in Keras.In [1]: import tensorflow as tfprint(tf.__version__) 2.0.0...…
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Introduction to TensorFlow
<!DOCTYPE html>Introduction to TensorFlow Introduction to TensorFlow¶Coding tutorials¶1. Hello TensorFlow!¶Hello TensorFlow!¶In [1]: # Import TensorFlowimport tensorflow as tf In [2]: ...…
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The Sequential model API
<!DOCTYPE html>Coding Tutorial In [2]: import tensorflow as tfprint(tf.__version__) 2.0.0The Sequential model API¶Coding tutorials¶1. Building a Sequential model¶2. Convolutional and pooling...…
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Optimizer, loss functions, metrics
<!DOCTYPE html>Metrics Metrics in Keras¶In this reading we will be exploring the different metrics in Keras that may be used to judge the performance of a model.In [1]: import tensorflow as tffrom tensorflow...…
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CNN classifier for the MNIST dataset
<!DOCTYPE html>Week 2 Programming Assignment Programming Assignment¶CNN classifier for the MNIST dataset¶Instructions¶In this notebook, you will write code to build, compile and fit a convolutional neural ...…
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Adding weight initialisers
<!DOCTYPE html>Weight Initializers Weight and bias initialisers¶In this reading we investigate different ways to initialise weights and biases in the layers of neural networks.In [1]: %matplotlib inlineimpor...…
