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7 changes: 2 additions & 5 deletions ...eature Store and Model Registry/End-to-end ML with Feature Store and Model Registry.ipynb
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"\n",
"This notebook demonstrates an end-to-end ML experiment cycle including feature creation, training data generation, model training and inference. The workflow touches on key Snowflake ML features including [Snowflake Feature Store](https://docs.snowflake.com/en/developer-guide/snowpark-ml/feature-store/overview), [Dataset](https://docs.snowflake.com/en/developer-guide/snowpark-ml/dataset), ML Lineage, [Snowpark ML Modeling](https://docs.snowflake.com/en/developer-guide/snowpark-ml/modeling) and [Snowflake Model Registry](https://docs.snowflake.com/en/developer-guide/snowpark-ml/model-registry/overview). \n",
"\n",
"Note: there may be a delay in the availability of the newest snowflake-ml-python package in the Snowflake Conda channel. To install the latest snowflake-ml-python package which includes all of necessary components used in this notebook, please follow the install instructions [here](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update).\n",
"\n",
"**Table of contents**\n",
"- [Set up test environment](#setup-test-env)\n",
" - [Install snowflake-ml-python](#install-package)\n",
" - [Connect to Snowflake](#connect-to-snowflake)\n",
" - [Select your example](#select-your-example)\n",
"- [Create features with Feature Store](#create-features-with-feature-store)\n",
Expand All @@ -46,10 +47,6 @@
"<a id='setup-test-env'></a>\n",
"## Set up test environment\n",
"\n",
"<a id='install-package'></a>\n",
"### Install snowflake-ml-python\n",
"You can follow **[here](https://docs.snowflake.com/en/developer-guide/snowpark-ml/overview)** to install *snowflake-ml-python* package which includes all of necessary components used in this notebook. The package in conda channel usually delayed by ~3 weeks from our latest release. You can follow this **[guide](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)** if you want to get the latest version as soon as it available.\n",
"\n",
"<a id='connect-to-snowflake'></a>\n",
"### Connect to Snowflake\n",
"\n",
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10 changes: 4 additions & 6 deletions Feature Store API Overview/Feature Store API Overview.ipynb
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"source": [
"# Feature Store API Overview\n",
"\n",
"This notebook provides an overview of Feature Store APIs. It demonstrates how to manage Feature Store, Feature Views, Feature Entities and how to retrieve features and generate training datasets etc. The goal is to provide a quick walkthrough of the most common APIs. For a full list of APIs, please refer to [API Reference page](https://docs.snowflake.com/en/developer-guide/snowpark-ml/reference/latest/feature_store)."
"This notebook provides an overview of Feature Store APIs. It demonstrates how to manage Feature Store, Feature Views, Feature Entities and how to retrieve features and generate training datasets etc. The goal is to provide a quick walkthrough of the most common APIs. For a full list of APIs, please refer to [API Reference page](https://docs.snowflake.com/en/developer-guide/snowpark-ml/reference/latest/feature_store).\n",
"\n",
"\n",
"Note: there may be a delay in the availability of the newest snowflake-ml-python package in the Snowflake Conda channel. To install the latest snowflake-ml-python package which includes all of necessary components used in this notebook, please follow the install instructions [here](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Table of contents**:\n",
"- [Install snowflake-ml-python](#install-package)\n",
"- [Set up connection and test dataset](#setup-test-environment)\n",
"- [Manage features in Feature Store](#manage-features-in-feature-store)\n",
" - [Initialize a Feature Store](#initialize-a-feature-store)\n",
Expand All @@ -43,10 +45,6 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"<a id='install-package'></a>\n",
"## Install snowflake-ml-python\n",
"You can follow **[here](https://docs.snowflake.com/en/developer-guide/snowpark-ml/overview)** to install *snowflake-ml-python* package which includes all of necessary components used in this notebook. The package in conda channel usually delayed by ~3 weeks from our latest release. You can follow this **[guide](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)** if you want to get the latest version as soon as it available.\n",
"\n",
"<a id='setup-test-environment'></a>\n",
"## Set up connection and test dataset\n",
"\n",
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21 changes: 9 additions & 12 deletions ML Lineage Workflows/ML Lineage Workflows.ipynb
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"This notebook showcases various machine learning workflows, delving into the lineage of each process. It highlights essential features of Snowflake's ML, including [Snowflake Feature Store](https://docs.snowflake.com/en/developer-guide/snowpark-ml/feature-store/overview), [Dataset](https://docs.snowflake.com/en/developer-guide/snowpark-ml/dataset), ML Lineage, [Snowpark ML Modeling](https://docs.snowflake.com/en/developer-guide/snowpark-ml/modeling) and [Snowflake Model Registry](https://docs.snowflake.com/en/developer-guide/snowpark-ml/model-registry/overview). \n",
"\n",
"\n",
"Note: there may be a delay in the availability of the newest snowflake-ml-python package in the Snowflake Conda channel. To install the latest snowflake-ml-python package which includes all of necessary components used in this notebook, please follow the install instructions [here](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update).\n",
"\n",
"**Table of contents**\n",
"\n",
"1. [Set up environment](#set-up-environment) \n",
" 1.1. [Install snowflake-ml-python](#install-package) \n",
" 1.2. [Connect to Snowflake](#connect-to-snowflake) \n",
" 1.3. [Select your example](#select-your-example) \n",
" 1.1. [Connect to Snowflake](#connect-to-snowflake) \n",
" 1.2. [Select your example](#select-your-example) \n",
"\n",
"2. [Feature View Lineage](#feature-view-lineage) \n",
"\n",
"3. [Training Data Lineage](#training-data-lineage) \n",
" 3.1. [Training data from feature views](#training-data-from-feature-views) \n",
" 3.1.1. [Dataset as training data](#dataset-as-training-data) \n",
" 3.1.2. [Tables as training data](#tables-as-training-data) \n",
" 3.1. [Training data from feature views](#training-data-from-feature-views) \n",
" 3.1.1. [Dataset as training data](#dataset-as-training-data) \n",
" 3.1.2. [Tables as training data](#tables-as-training-data) \n",
" 3.2. [Training data from source tables](#training-data-from-source-tables) \n",
" 3.2.1. [Dataset from source table as training data](#dataset-from-source-table-as-training-data) \n",
"\n",
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"id": "bb535ff6",
"metadata": {},
"source": [
"<a id='install-package'></a>\n",
"### 1.1 Install snowflake-ml-python\n",
"You can follow **[here](https://docs.snowflake.com/en/developer-guide/snowpark-ml/overview)** to install *snowflake-ml-python* package which includes all of necessary components used in this notebook. The package in conda channel usually delayed by ~3 weeks from our latest release. You can follow this **[guide](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)** if you want to get the latest version as soon as it available.\n",
"\n",
"### 1.2 Connect to Snowflake {-}\n",
"### 1.1 Connect to Snowflake {-}\n",
"\n",
"Let's start with setting up our test environment. We will create a session and a schema. The schema `FS_DEMO_SCHEMA` will be used as the Feature Store. It will be cleaned up at the end of the demo. You need to fill the `connection_parameters` with your Snowflake connection information. Follow this **[guide](https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-session)** for more details about how to connect to Snowflake.\n"
]
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"source": [
"<a id='select-your-example'></a>\n",
"\n",
"### 1.3 Select your example {-}\n",
"### 1.2 Select your example {-}\n",
"\n",
"We have prepared some examples that you can find in our [open source repo](https://github.com/snowflakedb/snowflake-ml-python/tree/main/snowflake/ml/feature_store/examples). Each example contains the source dataset, feature view and entity definitions which will be used in this demo. `ExampleHelper` (included in snowflake-ml-python) will setup everything with simple APIs and you don't have to worry about the details.\n",
"\n",
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6 changes: 2 additions & 4 deletions Manage features in DBT with Feature Store/Manage features in DBT with Feature Store.ipynb
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"source": [
"# Manage features in DBT with Feature Store\n",
"\n",
"This notebook showcases the interoperation between DBT and Snowflake Feature Store. The source data is managed in Snowflake database, while the feature pipelines are managed and executed from DBT. The output is stored as feature tables in Snowflake. Then We read from the feature tables and register them as external Feature View.\n",
"This notebook showcases the interoperation between DBT and Snowflake Feature Store. The source data is managed in Snowflake database, while the feature pipelines are managed and executed from DBT. The output is stored as feature tables in Snowflake. Then We read from the feature tables and register them as external Feature View. \n",
"\n",
"This demo requires DBT account.\n",
"\n",
"\n",
"## Install snowflake-ml-python\n",
"You can follow **[here](https://docs.snowflake.com/en/developer-guide/snowpark-ml/overview)** to install *snowflake-ml-python* package which includes all of necessary components used in this notebook. The package in conda channel usually delayed by ~3 weeks from our latest release. You can follow this **[guide](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)** if you want to get the latest version as soon as it available.\n"
"Note: there may be a delay in the availability of the newest snowflake-ml-python package in the Snowflake Conda channel. To install the latest snowflake-ml-python package which includes all of necessary components used in this notebook, please follow the install instructions [here](https://docs.snowflake.com/LIMITEDACCESS/snowpark-ml-library-update)."
]
},
{
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