Originally published at: https://developer.nvidia.com/blog/input-and-output-configurability-in-rapids-cuml/
The RAPIDS machine learning library, cuML, supports several types of input data formats while attempting to return results in the output format that fits best into users’ workflows. The RAPIDS team has added functionality to cuML to support diverse types of users: Figure 1: An example optimized cuML workflow. Maximize compatibility Users with existing NumPy,…