Machine Learning Engineer with an interest in robotics, natural language processing and computer vision.
Have worked on various projects, such as driver assistance systems, recommender systems, word sense disambiguation, and others.
Author of several small open source packages, and have made small contributions to open source projects, such as ANTLR and Tensorflow.
Memory-mapped files are an underused tool in machine learning projects, which offer very fast I/O operations, making them suitable for storing datasets during training that don't fit into memory.
In this talk, we will discuss the benefits of using memory maps, their downsides, and how to address them.