The Oracle Cloud Infrastructure (OCI) Data Science product management team is maintaining a series of demos, tutorials, and code examples highlighting the different features of both OCI Data Science and AI services.
Each directory in this repo corresponds to a different demo/lab and contains its own separate README file giving you instructions on how to run the code examples.
- labs In this directory we have 4 different examples to do things like end-to-end build, train, deploy and invoke a machine learning model using OCI Data Science services.
- ads_v_2_2_0 This directory has all of our generic ADS notebook examples. Here, for example, you can find a notebook about vault connection and model deployment.
- environment_examples This directory has subdirectories for the different conda environments offered. Within each subdirectory you will find notebook examples on that topic.
- model_deployment_examples Here we have several different examples of model deployments, we have offered sample runtime.yaml and score.py files on several different topics.
- knowledge_base Directory with tips and tricks on a variety of topics.
There are several ways you can access OCI Data Science documentation:
- our official OCI Data Science service documentation site
- our YouTube playlist
- our AI & Data Science blog
If you want to know more about Oracle Accelerated Data Science (ADS) Python SDK, please visit our ADS user documentation website.
- Create a github issue.
This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide.
Please consult the security guide for our responsible security vulnerability disclosure process.
Copyright (c) 2021 Oracle and/or its affiliates.
Released under the Universal Permissive License v1.0 as shown at https://oss.oracle.com/licenses/upl/.