Using Learning Rate Schedules for Deep Learning Models in Python with Keras - Machine Learning Mastery

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 you will discover how you can use different learning rate schedules for your neural network models in Python using the Keras deep learning library. Using Learning Rate Schedules for Deep Learning Models in Python with Keras Photo by Columbia GSAPP, some rights reserved.