snowflake-ai 0.1.0

A Snowflake centic Enterprise AI/ML framework with tight integration of popular data science libraries

Snowflake-AI

Snowflake_AI is a Snowflake-centric Enterprise AI/ML framework with tight integration of popular Python data science libraries, e.g., Pandas, Scikit-Learn, Tensorflow, Pytorch, MLFlow, etc. This project simplifies the process of integrating your company's Snowflake data with those popular libraries, making it easier to develop and deploy machine learning models.

Installation

Before getting started, ensure you have Poetry installed on your system. You can install Poetry by following the instructions here.

Next, clone this repository and navigate to the project directory (assume you are in bash terminal):

git clone https://github.com/tonyxliu/snowflake-ai.git
cd snowflake-ai

Then, use Poetry to install all dependencies:

poetry install

Configuration

Copy the sample configuration file and update the Snowflake connection parameters:

mkdir -p ~/snowflake_ai/conf
cp snowflake_ai/conf/app_config.toml ~/snowflake-ai/conf/

Edit snowflake_ai/conf/app_config.toml with your Snowflake connection details.

Usage

To get started with Snowflake-AI, import SnowConnect and DataFrameFactory from the library:

from snowflake_ai.common import SnowConnect
from snowflake_ai.common import DataFrameFactory

Create a SnowConnect instance:

connect = SnowConnect()

Specify the table/view or sql you want to work with and create a DataFrame:

tbl_nm = 'SNOWFLAKE_SAMPLE_DATA.TPCH_SF1.CUSTOMER'
sdf = DataFrameFactory.create_df(tbl_nm, connect)

Display the contents of the DataFrame:

sdf.show()

From here, you can use Snowflake-AI to preprocess and manipulate your data using Pandas and Scikit-Learn, train machine learning models, and perform predictions. Stay tuned, as there are many features in the pipelines waiting to be released.

Enjoy building your next AI/ML project with Snowflake-AI!

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.