Author Archive | Jason Brownlee

How to Make Classification and Regression Predictions for Deep Learning Models in Keras

How to Make Predictions with Keras

Once you choose and fit a final deep learning model in Keras, you can use it to make predictions on new data instances. There is some confusion amongst beginners about how exactly to do this. I often see questions such as: How do I make predictions with my model in Keras? In this tutorial, you […]

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Why Initialize a Neural Network with Random Weights?

Why Initialize a Neural Network with Random Weights?

The weights of artificial neural networks must be initialized to small random numbers. This is because this is an expectation of the stochastic optimization algorithm used to train the model, called stochastic gradient descent. To understand this approach to problem solving, you must first understand the role of nondeterministic and randomized algorithms as well as […]

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Example MNIST images

Image Augmentation for Deep Learning with Keras

Data preparation is required when working with neural networks and deep learning models. Increasingly, data augmentation is also required on more complex object recognition tasks. In this post, you will discover how to use data preparation and data augmentation with your image datasets when developing and evaluating deep learning models in Python with Keras. After […]

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Using Learning Rate Schedules for Deep Learning Models in Python with Keras

Using Learning Rate Schedules for Deep Learning Models in Python with Keras

Training a neural network or large deep learning model is a difficult optimization task. The classical algorithm to train neural networks is called stochastic gradient descent. It has been well established that you can achieve increased performance and faster training on some problems by using a learning rate that changes during training. In this post, […]

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