Snowflake Feature Store and Datasets
Snowflake
| Expert
- 14 videos | 1h 58m 3s
- Includes Assessment
- Earns a Badge
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
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Discover the key concepts covered in this courseOutline the features and uses of snowflake datasetsMaterialize a dataframe to a dataset and create and consume versions of the datasetCreate a snowflake ml pipeline for logistic regressionCreate tags and associate metrics and a tag with a modelUtilize snowpark-optimized warehouses and grid search for hyperparameter tuningRegister a model with tuned hyperparameter values with the model registry
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Identify the need for the snowflake feature store and analyze how feature views and entities workOutline types of feature views and how entities are associated with feature viewsCreate a feature store and entity using snowpark apisCreate a managed feature view and analyze the implementation as a dynamic tableCreate an external feature view, join two feature views, and query for all feature views associated with a specific entityRecognize the workflow for using feature stores and highlight the benefits of this workflowSummarize the key concepts covered in this course
IN THIS COURSE
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1m 49sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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4m 53sUpon completion of this video, you will be able to outline the features and uses of Snowflake Datasets. FREE ACCESS
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10m 5sDiscover how to materialize a DataFrame to a dataset and create and consume versions of the dataset. FREE ACCESS
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7m 52sDuring this video, you will learn how to create a Snowflake ML pipeline for logistic regression. FREE ACCESS
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11m 26sIn this video, find out how to create tags and associate metrics and a tag with a model. FREE ACCESS
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13m 2sIn this video, discover how to utilize Snowpark-optimized warehouses and grid search for hyperparameter tuning. FREE ACCESS
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9m 27sLearn how to register a model with tuned hyperparameter values with the model registry. FREE ACCESS
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9m 22sAfter 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
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9m 15sUpon completion of this video, you will be able to outline types of feature views and how entities are associated with feature views. FREE ACCESS
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10m 41sDuring this video, discover how to create a feature store and entity using Snowpark APIs. FREE ACCESS
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9m 41sIn this video, you will learn how to create a managed feature view and analyze the implementation as a dynamic table. FREE ACCESS
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12m 37sFind 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
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5m 51sAfter completing this video, you will be able to recognize the workflow for using feature stores and highlight the benefits of this workflow. FREE ACCESS
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2m 1sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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