Lessons Learned from Deploying Deep Learning at Scale

Deep learning is a machine learning technique used to solve complex problems related to image recognition, natural language processing, and more. It requires both massive amounts of data and computational power. The compute problem has been solved largely by GPUs, which have become essential for making deep learning performant. GPUs have reduced the time required to train models from weeks to days. Most training tasks can be accomplished by building your own box.