You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
馃挕 [REQUEST] - <title>An inbuilt function to retrieve a list of datasets categorised by problem type (e.g., classification, regression, clustering).
#2630
PyTorch has inbuilt function to list all datasets.
`import torchvision.datasets as datasets
//Get a list of all datasets
all_datasets = datasets.all
//Print the list of datasets
print(all_datasets)
`
Rather than focusing on getting all the dataset, we can include a parameter. Parameter will take the type of task person wants to do e.g Clustering, Regression, Classification. After putting parameter all the related dataset according to task will be shown.
Overall, a built-in function to retrieve a list of datasets categorised by problem type would be a valuable addition to PyTorch. It would make it easier for users to find, discover, use, and share datasets.
Existing tutorials on this topic
No response
Additional context
No response
The content you are editing has changed. Please copy your edits and refresh the page.
馃殌 Descirbe the improvement or the new tutorial
PyTorch has inbuilt function to list all datasets.
`import torchvision.datasets as datasets
//Get a list of all datasets
all_datasets = datasets.all
//Print the list of datasets
print(all_datasets)
`
Rather than focusing on getting all the dataset, we can include a parameter. Parameter will take the type of task person wants to do e.g Clustering, Regression, Classification. After putting parameter all the related dataset according to task will be shown.
Overall, a built-in function to retrieve a list of datasets categorised by problem type would be a valuable addition to PyTorch. It would make it easier for users to find, discover, use, and share datasets.
Existing tutorials on this topic
No response
Additional context
No response
Tasks
Tasks
Tasks
The text was updated successfully, but these errors were encountered: