The C3 AI Suite provides researchers many tools to analyze data and build and deploy machine learning models. To get started using the C3 AI Suite, please follow the C3.ai DTI Quickstart guide. This guide explains how to connect to a C3.ai cluster, access data using C3.ai methods, and convert C3.ai method outputs to an easy-to-analyze form. Additionally, the guide also provides more detailed instructions to DTI members using the Covid-19 DataLake. Examples in this guide work using the base Datalake available in the git repository: https://github.com/c3aidti/dtiTraining
Please note, this guide covers how to run read-only queries on the C3 AI Suite. For more advanced topics, such as loading data, building metrics, or configuring and training machine learning models, please refer to the following wikis:
- Data Integration (Not yet available)
- Metrics (Not yet available)
- Machine Learning (Not yet available)
Provision a C3 Package
Provision your C3 package to your C3 cluster/tenant/tag following the instructions available at the DTI Provisioning Guide. DTI members wishing to execute the examples in this guide should provision the 'baseCovidDataLake' using the special instructions in the guide.
Connect to a C3.ai cluster
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To learn more about the differences between 'evalMetrics' and 'evalMetricsWithMetadata' see the C3.ai Developer Documentation here: https://developer.c3.ai/docs/7.12.0/type/MetricEvaluatable
To evaluate a metric, users must provide the following parameters (called an EvalMetricSpec) to the 'evalMetrics' or 'evalMetricsWithMetadata' methods.
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To learn more about evaluating and visualizing metrics, please see the C3.ai Developer Documentation here:
- https://developer.c3.ai/docs/7.12.17/topic/metrics-evaluating-metrics
- https://developer.c3.ai/docs/7.12.17/topic/metrics-visualizing-metrics
- https://developer.c3.ai/docs/7.12.0/topic/ds-jupyter-notebooks
Note: Metrics can only be evaluated on C3.ai Types that mix in the 'MetricEvaluatable' Type.
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