A Simple Solution for Managing Cloud-Based ML-Training
How to Implement a Custom Training Solution Using Basic (Unmanaged) Cloud Service APIs`Photo by Aditya Chinchure on UnsplashIn previous posts (e.g., here) we have expanded on the benefits of developing AI models in the cloud. Machine Learning projects, especially large ones, typically require access to specialized machinery (e.g., training accelerators), the ability to scale at will, an appropriate infrastructure for maintaining large amounts of data, and tools for managing large-scale experimentation. Cloud service…