The Oracle Accelerated Data Science (ADS) SDK used by data scientists and analysts for data exploration and experimental machine learning to democratize machine learning and analytics by providing easy-to-use, performant, and user friendly tools that brings together the best of data science practices.
The ADS SDK helps you connect to different data sources, perform exploratory data analysis, data visualization, feature engineering, model training, model evaluation, and model interpretation. ADS also allows you to connect to the model catalog to save and load models to and from the catalog.
- Open a GitHub issue for bug reports, questions, or requests for enhancements.
- Report a security vulnerability according to the Reporting Vulnerabilities guide.
These are the minimum required steps to install and set up the ADS SDK to run on your local machine for development and testing purposes.
Install Anaconda from https://repo.continuum.io/miniconda/
for the operating system you are using.
In the terminal client, enter the following where is the name you want to call your environment, and set the Python version you want to use. ADS SDK requires Python >=3.7.
conda create -n <yourenvname> python=3.7 anaconda
This installs the Python version and all the associated anaconda packaged libraries at path_to_your_anaconda_location/anaconda/envs/<yourenvname>
To activate or switch into your conda environment, run this command:
conda activate <yourenvname>
To list of all your environments, use the conda env list
command.
Open the destination folder where you want to clone ADS library, and install dependencies like this:
cd <desctination_folder>
git clone [email protected]:oracle/accelerated-data-science.git
python3 -m pip install -e .
To which packages were installed and their version numbers, run:
python3 -m pip freeze
You should also set up configuration files, see the SDK and CLI Configuration File.
Use ads_version.json
for versioning. The ADS SDK is packaged as a wheel. To generate the wheel, you can run:
python3 setup.py sdist bdist_wheel
This wheel can then be installed using pip
.
Consult the security guide for our responsible security vulnerability disclosure process.
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