NSML: Meet the MLaaS platform with a real-world case study
This work addresses the need for better collaboration and management tools in machine learning for industries and academies, though it appears incremental as it builds on existing MLaaS concepts.
The authors tackled the limitations of existing machine learning frameworks in supporting collaboration and management for data and models by proposing NSML, a Machine Learning as a Service (MLaaS) platform, which was validated through experiments with common examples and three real-world competitions.
The boom of deep learning induced many industries and academies to introduce machine learning based approaches into their concern, competitively. However, existing machine learning frameworks are limited to sufficiently fulfill the collaboration and management for both data and models. We proposed NSML, a machine learning as a service (MLaaS) platform, to meet these demands. NSML helps machine learning work be easily launched on a NSML cluster and provides a collaborative environment which can afford development at enterprise scale. Finally, NSML users can deploy their own commercial services with NSML cluster. In addition, NSML furnishes convenient visualization tools which assist the users in analyzing their work. To verify the usefulness and accessibility of NSML, we performed some experiments with common examples. Furthermore, we examined the collaborative advantages of NSML through three competitions with real-world use cases.