Kaptain offers several ways to train models (incl. distributed), tune hyperparameters, and deploy optimized models that autoscale.
The Kaptain SDK is the best choice for a data science-friendly user experience. It is designed to be a great first experience with Kaptain.
If you prefer to have full control and are familiar and comfortable with Kubeflow SDKs, or YAML specifications in Kubernetes, then we suggest you consult the other tutorials.
Note that everything can be done from within notebooks, thanks to Kaptain’s notebooks-first approach to machine learning.
Tutorial for Kaptain SDK…Read More
Tutorials for model development and distributed training with TensorFlow, PyTorch, and MXNet…Read More
Tutorial for Hyperparameter Tuning…Read More
End-to-end Pipeline with KFServing
Tutorial for End-to-end Pipeline with KFServing…Read More
Tutorial for Metadata SDK…Read More
Tutorial for Kubeflow Fairing…Read More