Mark Ryan has 20 years of experience leading technical teams in the areas of relational databases and machine learning. He is a Data Science Manager at Intact, where he leads teams applying machine learning to real business problems, drawing on a deep background that stretches from database internals to modern deep learning.

Mark is a prominent advocate for using deep learning on structured, tabular data, a domain many practitioners still reserve for classical methods. He is the author of Deep Learning with Structured Data, which makes the case for when and how to apply deep learning to tabular problems such as fraud detection, and Deep Learning with fastai Cookbook, a hands-on guide to training models with fastai. More recently he co-authored Machine Learning for Tabular Data with Luca Massaron, covering gradient boosting with XGBoost and LightGBM alongside deep learning with TensorFlow and PyTorch for common business data sources.

A repeated Book of the Week guest on DataTalksClub, Mark combines decades of technical leadership with a clear, practical writing style that helps engineers and data scientists bring the latest ML techniques into production.