.. meta:: :description lang=en: Oracle Accelerated Data Science SDK (ORACLE-ADS) is a Python library that is part of the Oracle Cloud Infrastructure Data Science service. ORACLE-ADS is the client library and CLI for Machine learning engineers to work with Cloud Infrastructure (CPU and GPU VMs, Storage etc, Spark) for Data, Models, Notebooks, Pipelines and Jobs. Oracle Accelerated Data Science (ADS) ===================================== |PyPI|_ |Python|_ |Notebook Examples|_ .. |PyPI| image:: https://img.shields.io/pypi/v/oracle-ads.svg?style=for-the-badge&logo=pypi&logoColor=white .. _PyPI: https://pypi.org/project/oracle-ads/ .. |Python| image:: https://img.shields.io/pypi/pyversions/oracle-ads.svg?style=for-the-badge&logo=pypi&logoColor=white .. _Python: https://pypi.org/project/oracle-ads/ .. |Notebook Examples| image:: https://img.shields.io/badge/docs-notebook--examples-blue?style=for-the-badge&logo=pypi&logoColor=white .. _Notebook Examples: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples .. toctree:: :hidden: :maxdepth: 5 :caption: Getting Started: release_notes user_guide/quick_start/quick_start .. toctree:: :hidden: :maxdepth: 5 :caption: Installation and Configuration: user_guide/cli/quickstart user_guide/cli/authentication user_guide/cli/opctl/configure user_guide/cli/opctl/local-development-setup .. toctree:: :hidden: :maxdepth: 5 :caption: Low-Code AI Operators: user_guide/operators/index user_guide/operators/common/index user_guide/operators/forecasting_operator/index user_guide/operators/anomaly_detection_operator/index user_guide/operators/pii_operator/index user_guide/operators/recommender_operator/index .. toctree:: :hidden: :maxdepth: 5 :caption: Tasks: user_guide/loading_data/connect user_guide/data_labeling/index user_guide/data_transformation/data_transformation user_guide/data_visualization/visualization user_guide/model_training/index user_guide/model_registration/introduction .. toctree:: :hidden: :maxdepth: 5 :caption: Integrations: user_guide/apachespark/spark user_guide/big_data_service/index user_guide/jobs/index user_guide/logs/logs user_guide/pipeline/index user_guide/large_language_model/index user_guide/secrets/index .. toctree:: :hidden: :maxdepth: 5 :caption: Classes: modules .. admonition:: Introducing AI Quick Actions :class: note Deploy, Fine Tune and Evaluate Large language models such as `Mistral-7B-Instruct-v0.2 `__, `CodeLlama-13b-Instruct-hf `__, etc with just a couple of clicks. Visit `AI Quick Actions documentation `__ for the latest information .. admonition:: Oracle Accelerated Data Science (ADS) :class: note Oracle Accelerated Data Science (ADS) is maintained by the Oracle Cloud Infrastructure Data Science service team. It speeds up common data science activities by providing tools that automate and/or simplify common data science tasks, along with providing a data scientist friendly pythonic interface to Oracle Cloud Infrastructure (OCI) services, most notably OCI Data Science, Data Flow, Object Storage, and the Autonomous Database. ADS gives you an interface to manage the lifecycle of machine learning models, from data acquisition to model evaluation, interpretation, and model deployment. With ADS you can: - Read datasets from Oracle Object Storage, Oracle RDBMS (ATP/ADW/On-prem), AWS S3, and other sources into Pandas dataframes. - Easily compute summary statistics on your dataframes and perform data profiling. - Tune models using hyperparameter optimization with the ADSTuner tool. - Generate detailed evaluation reports of your model candidates with the ADSEvaluator module. - Save machine learning models to the OCI Data Science Models. - Deploy those models as HTTPS endpoints with Model Deployment. - Launch distributed ETL, data processing, and model training jobs in Spark with OCI Data Flow. - Train machine learning models in OCI Data Science Jobs. - Manage the lifecycle of conda environments through the ads conda command line interface (CLI). - Distributed Training with PyTorch, Horovod and Dask .. admonition:: Installation :class: note python3 -m pip install oracle-ads .. admonition:: Source Code :class: note `https://github.com/oracle/accelerated-data-science `_ .. code-block:: python3 >>> import ads >>> ads.hello() .. runblock:: pycon >>> import ads >>> ads.hello() Additional Documentation ++++++++++++++++++++++++ - `OCI Data Science and AI services Examples `_ - `Oracle AI & Data Science Blog `_ - `OCI Documentation `_ - `OCIFS Documentation `_ - `Example Notebooks `_ Examples ++++++++ Load data from Object Storage ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: python3 import ads import oci import pandas as pd ads.set_auth( auth="api_key", oci_config_location=oci.config.DEFAULT_LOCATION, profile="DEFAULT" ) bucket_name = "" path = "" namespace = "" df = pd.read_csv( f"oci://{bucket_name}@{namespace}/{path}", storage_options=ads.auth.default_signer() ) Load data from Autonomous DB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This example uses SQL injection safe binding variables. .. code-block:: python3 import ads import pandas as pd connection_parameters = { "user_name": "", "password": "", "service_name": "", "wallet_location": "", } df = pd.DataFrame.ads.read_sql( """ SELECT * FROM SH.SALES WHERE ROWNUM <= :max_rows """, bind_variables={ max_rows : 100 }, connection_parameters=connection_parameters, ) More Examples ~~~~~~~~~~~~~ See :doc:`quick start` guide for more examples Contributing ++++++++++++ This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide `CONTRIBUTING.md `_. Find Getting Started instructions for developers in `README-development.md `_ Security ++++++++ Consult the security guide `SECURITY.md `_ for our responsible security vulnerability disclosure process. License +++++++ Copyright (c) 2020, 2022 Oracle and/or its affiliates. Licensed under the `Universal Permissive License v1.0 `_