Implement a partition strategy based on the data's size, as this is the most critical factor for machine learning workloads.

Create a partition strategy based on the data's natural partition key, such as feature attributes or categorical variables, to improve query performance and reduce the amount of data scanned.

Use a hash-based partitioning method to distribute the data evenly across multiple partitions, regardless of the data's characteristics.

Do not implement any partition strategy, as it is not necessary for machine learning workloads in Azure Data Lake Storage Gen2.