Dive into a comprehensive 58-minute conference talk by Xavier Amatriain on practical deep learning systems, presented at Full Stack Deep Learning in November 2019. Explore Amatriain's background and insights from his work at Qi, Netflix, and other tech companies. Learn about crucial aspects of deep learning, including data handling, transfer learning, fine-tuning, and the importance of simple models. Discover real-life examples, architecture engineering, and the differences between supervised and self-supervised learning. Examine topics such as data bias, fairness, and deploying models in production. Gain valuable knowledge on evaluation approaches, metrics, and machine learning infrastructure. Conclude with a comparison of deep learning and linear models, followed by a Q&A session.