Deep Learning with JavaScript

Chapter 6. Working with data

This chapter covers

• How to use the tf.data API to train models using large datasets
• Exploring your data to find and fix potential issues
• How to use data augmentation to create new “pseudo-examples” to improve model quality

The wide availability of large volumes of data is a major factor leading to today’s machine-learning revolution. Without easy access to large amounts of high-quality data, the dramatic rise in machine learning would not have happened. Datasets are now available all over the internet—freely shared on sites like Kaggle and OpenML, among others—as are benchmarks for state-of-the-art performance. Entire branches of machine learning have been propelled forward by the availability of “challenge” ...