Snowflake Feature Store and Datasets

Snowflake    |    Expert
  • 14 videos | 1h 58m 3s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Snowflake ML has now introduced Snowflake Feature Store, which can improve collaboration, break down data silos, and facilitate feature reuse. Datasets are another great new feature, offering data versioning to drive model result reproducibility. In this course, learn how to use Snowflake Datasets for various data operations, including materializing DataFrames into datasets and managing versions, building a Snowflake ML pipeline for logistic regression, and creating and applying model tags. Next, discover how to utilize Snowpark-optimized warehouses for hyperparameter tuning, register tuned models with the Snowflake Model Registry, and create feature stores and entities using Snowpark APIs. Finally, explore how to build managed feature views and the workflow of feature stores. After course completion, you will be able to use Snowflake Feature Store and datasets.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline the features and uses of snowflake datasets
    Materialize a dataframe to a dataset and create and consume versions of the dataset
    Create a snowflake ml pipeline for logistic regression
    Create tags and associate metrics and a tag with a model
    Utilize snowpark-optimized warehouses and grid search for hyperparameter tuning
    Register a model with tuned hyperparameter values with the model registry
  • Identify the need for the snowflake feature store and analyze how feature views and entities work
    Outline types of feature views and how entities are associated with feature views
    Create a feature store and entity using snowpark apis
    Create a managed feature view and analyze the implementation as a dynamic table
    Create an external feature view, join two feature views, and query for all feature views associated with a specific entity
    Recognize the workflow for using feature stores and highlight the benefits of this workflow
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 49s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 53s
    Upon completion of this video, you will be able to outline the features and uses of Snowflake Datasets. FREE ACCESS
  • Locked
    3.  Creating, Versioning, and Loading Datasets
    10m 5s
    Discover how to materialize a DataFrame to a dataset and create and consume versions of the dataset. FREE ACCESS
  • Locked
    4.  Building a Snowflake ML Pipeline for Logistic Regression
    7m 52s
    During this video, you will learn how to create a Snowflake ML pipeline for logistic regression. FREE ACCESS
  • Locked
    5.  Working with Tags and Versions
    11m 26s
    In this video, find out how to create tags and associate metrics and a tag with a model. FREE ACCESS
  • Locked
    6.  Utilizing Snowpark-optimized Warehouses and Hyperparameter Tuning
    13m 2s
    In this video, discover how to utilize Snowpark-optimized warehouses and grid search for hyperparameter tuning. FREE ACCESS
  • Locked
    7.  Using Tuned Models in Snowflake Pipelines
    9m 27s
    Learn how to register a model with tuned hyperparameter values with the model registry. FREE ACCESS
  • Locked
    8.  Feature Views and Entities
    9m 22s
    After completing this video, you will be able to identify the need for the Snowflake Feature Store and analyze how feature views and entities work. FREE ACCESS
  • Locked
    9.  Feature Stores and Feature Views
    9m 15s
    Upon completion of this video, you will be able to outline types of feature views and how entities are associated with feature views. FREE ACCESS
  • Locked
    10.  Creating Feature Stores and Entities
    10m 41s
    During this video, discover how to create a feature store and entity using Snowpark APIs. FREE ACCESS
  • Locked
    11.  Making a Managed Feature View
    9m 41s
    In this video, you will learn how to create a managed feature view and analyze the implementation as a dynamic table. FREE ACCESS
  • Locked
    12.  Creating External Feature Views and Joining Query Views
    12m 37s
    Find out how to create an external feature view, join two feature views, and query for all feature views associated with a specific entity. FREE ACCESS
  • Locked
    13.  The Workflow and Benefits of Feature Stores
    5m 51s
    After completing this video, you will be able to recognize the workflow for using feature stores and highlight the benefits of this workflow. FREE ACCESS
  • Locked
    14.  Course Summary
    2m 1s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Data Transformation Using the Snowpark API
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Course Continuous Data Pipelines and Dynamic Tables in Snowflake
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Course Snowpark ML APIs and the Model Registry