Model Development

The C3 AI Suite platform provides data science teams with un-compromised flexibility in building and testing machine learning models based on prepackaged templates that use the latest open-source frameworks and’s ML Pipeline technology.

  • Use the model-driven architecture to manage and scale AI/ML model development
  • Compare models from Python, R, Spark with the same API​
  • Generate better models using Auto ML capabilities
  • Train on all data using distributed architecture of the C3 AI Suite platform

ML Pipelines

  • Leverage library of 30 pre-built ML pipes on the C3 AI Suite and choose from a selection of deep learning, natural language processing, forecasting, and tree-based model pipes​
  • Link composable ML pipes together to solve more complex uses cases​
  • Wrap your existing models in a custom ML Pipeline to operate at scale​
  • Use automatic model management including scoring, interpretability, model version, and validation

Auto ML

Auto ML

  • Run pre-packaged experiments to automate and scale-out time-intensive processes like parallelized model training and hyperparameter optimization.​
  • Choose the best approach for your hyperparameter optimization experiment, including randomized, grid, or Bayesian optimization.​
  • Parallelize experiments across the auto-scaling cluster or specify resource requirements such as CPU vs. GPU.​
  • Track all experiments in C3 AI ML Studio’s visual experiment tool​