Democratizing Machine Learning at Scale with Kubernetes on Azure - The New Stack

Microsoft sponsored this article, which was written by The New Stack. Containers and the Kubernetes orchestrator are emerging as core technologies for delivering distributed training at the scale that effective machine learning requires to be reliable in production use cases. Massive labeled datasets and the tools to work with them have driven the rise of machine learning from obscure research technique to mainstream technology. Years of gradual improvements in algorithms have been bundled into frameworks like TensorFlow and PyTorch, and using the massive parallelism of GPUs speeds up the process of training those algorithms. Containers have their own tradeoffs but with the right tools and cloud scale, they're showing real promise in scale-out architectures to support distributed machine learning environments.