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…

In this tutorial, you will learn how to use Cyclical Learning Rates (CLR) and Keras to train your own neural networks. Using Cyclical Learning Rates you can dramatically reduce the number of experiments required to tune and find an optimal…

In this tutorial, you will learn about learning rate schedules and decay using Keras. You’ll learn how to use Keras’ standard learning rate decay along with step-based, linear, and polynomial learning rate schedules. When training a neural network, the learning…

In this tutorial, you will learn how to perform video classification using Keras, Python, and Deep Learning. Specifically, you will learn: The difference between video classification and standard image classification How to train a Convolutional Neural Network using Keras for…

In today’s tutorial, you will learn how to use Keras’ ImageDataGenerator class to perform data augmentation. I’ll also dispel common confusions surrounding what data augmentation is, why we use data augmentation, and what it does/does not do. Having a dataset…

In this tutorial, you will learn how to change the input shape tensor dimensions for fine-tuning using Keras. After going through this guide you’ll understand how to apply transfer learning to images with different image dimensions than what the CNN…

In this tutorial, you will learn how to perform online/incremental learning with Keras and Creme on datasets too large to fit into memory. A few weeks ago I showed you how to use Keras for feature extraction and online learning…

In this tutorial, you will learn how to use Keras and Mask R-CNN to perform instance segmentation (both with and without a GPU). For developing and fine-tuning Mask R-CNN models, having access to rich, diverse datasets is critical. These datasets…

In this tutorial, you will learn how to perform fine-tuning with Keras and Deep Learning. We will take a CNN pre-trained on the ImageNet dataset and fine-tune it to perform image classification and recognize classes it was never trained on.…