Tag Archives | neural nets

Label smoothing with Keras, TensorFlow, and Deep Learning

In this tutorial, you will learn two ways to implement label smoothing using Keras, TensorFlow, and Deep Learning. When training your own custom deep neural networks there are two critical questions that you should constantly be asking yourself: Am I overfitting to my training data? Will my model generalize to data outside my training and […]

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3 ways to create a Keras model with TensorFlow 2.0 (Sequential, Functional, and Model Subclassing)

Keras and TensorFlow 2.0 provide you with three methods to implement your own neural network architectures: Sequential API Functional API Model subclassing Inside of this tutorial you’ll learn how to utilize each of these methods, including how to choose the right API for the job. To learn more about Sequential, Functional, and Model subclassing with […]

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Why is my validation loss lower than my training loss?

In this tutorial, you will learn the three primary reasons your validation loss may be lower than your training loss when training your own custom deep neural networks. I first became interested in studying machine learning and neural networks in late high school. Back then there weren’t many accessible machine learning libraries — and there […]

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Keras Learning Rate Finder

In this tutorial, you will learn how to automatically find learning rates using Keras. This guide provides a Keras implementation of fast.ai’s popular “lr_find” method. Today is part three in our three-part series of learning rate schedules, policies, and decay using Keras: Part #1: Keras learning rate schedules and decay Part #2: Cyclical Learning Rates […]

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