Artificial IntelligenceImprove your machine learning training routine with cloud-based, containerized workflows
Training machine learning models on a local machine in a notebook is a common task among data scientists. It is the easiest way to get started, experiment and build a first working model. But for most businesses this is not a satisfying option: Today, making the most of your training data usually means to scale to gigabytes or petabytes of data, which do not easily fit into your local machine. Data is your most valuable asset and you would not want to use only small fraction of it due to technical reasons.
