Train Custom Model
Create and train a custom model. The request must include a source parameter that is either an externally accessible Azure storage blob container Uri (preferably a Shared Access Signature Uri) or valid path to a data folder in a locally mounted drive. When local paths are specified, they must follow the Linux/Unix path format and be an absolute path rooted to the input mount configuration setting value e.g., if '{Mounts:Input}' configuration setting value is '/input' then a valid source path would be '/input/contosodataset'. All data to be trained is expected to be under the source folder or sub folders under it. Models are trained using documents that are of the following content type - 'application/pdf', 'image/jpeg', 'image/png', 'image/tiff'. Other type of content is ignored.
Request body
Response
Request is queued successfully.