deeplizard shows us how to add batch normalization to a convolutional neural network.
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deeplizard teaches us how to set up debugging for PyTorch source code in Visual Studio Code.
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deeplizard debugs the PyTorch DataLoader to see how data is pulled from a PyTorch data set and is normalized.
We see the impact of several of the constructor parameters and see how the batch is built.
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edureka! streamed this Azure ML tutorial this morning.
deeplizard teaches us how to normalize a dataset. We’ll see how dataset normalization is carried out in code, and we’ll see how normalization affects the neural network training process.
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deeplizard demonstrates how to process numerical data that we’ll later use to train our very first artificial neural network in this video.
In this video, deeplizard discusses GPU support for TensorFlow and the integrated Keras API and how to get your code running with a GPU.
deeplizard demonstrates how we can use the CUDA capabilities of PyTorch to run code on the GPU in this episode.
In this episode, deeplizard discusses the Keras integration with TensorFlow (tf.keras), compatibility requirements, and how to get Keras installed on your machine!
deeplizard has put together a course on how to use Keras.
In this course, we will learn how to use Keras, a neural network API written in Python! In this episode, we discuss the prerequisites required to start working with Keras, why Keras is a good library to learn, and what resources you’ll have available to ensure your success in this course.
