What is one of the available shapes for Data Science Notebook Sessions?

The selection of VM.Standard2.16 as one of the available shapes for Data Science Notebook Sessions highlights the need for computational resources that can effectively manage the demands of data science tasks. This particular shape offers a balanced configuration that typically includes a reasonable CPU count and a significant amount of memory, making it suitable for performing complex computations, running data analyses, and handling large datasets.

Data Science Notebook Sessions are often resource-intensive, as they may involve tasks such as data cleaning, model training, and visualization, all of which benefit from more CPUs and memory. VM.Standard2.16 strikes a good balance for many typical data science workloads, which is why it stands out as a viable option in terms of performance and cost-efficiency.

In the context of other available configurations, this shape is often chosen to ensure that users can carry out a broad range of data science operations without being hindered by resource limitations.