Question: How do you manually remove a classification from an asset?
This article from Purview team gives many details on editing an asset's values, but I don't see how to manually remove a classification from an asset.
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I just finished training a Custom Azure Translate Model with a set of 10.000 sentences. I now have the options to review the result and test the data. While I already get a good result score I would like to continue training the same model with additional data sets before publishing. I cant find any information regarding this in the documentation.
The only remotely close option I can see is to duplicate the first model and add the new data sets but this would create a new model and not advance the original one.
Once the project is created, we can train with different models on different datasets. Once the dataset is uploaded and the model was trained, we cannot modify the content of the dataset or upgrade it.
https://learn.microsoft.com/en-us/azure/cognitive-services/translator/custom-translator/quickstart-build-deploy-custom-model
The above document can help you.
I’m performing a series of experiments with Azure AutoML and I need to see the featurized data. I mean, not just the new features names retrieved by method get_engineered_feature_names() or the featurization details retrieved by get_featurization_summary(), I refer to the whole transformed dataset, the one obtained after scaling/normalization/featurization that is therefore used to train the models.
Is it possible to access to this dataset or download it as a file?
Thanks.
Microsoft expert confirmed that currently they "don't store the dataset from scaling/normalization/featurization after the run is complete". Answer here.
I have been using the form recognizer service and form labeller tool, using the version 2 of the api, to train my models to read a set of forms. But i have the need to use more than one layout of the forms, not knowing which form (pdf) layout is being uploaded.
Is it as simple as labelling the different layouts within the same model. Or is there another way to identify which model is to be used with which form.?
any help greatly appreciated
This is a common request. for now, if the 2 forms styles are not that different, you could try to train one model and see if that model could correctly extract key/value. Another option is to train two different forms, you could write a simple classification program to decide which model to use.
Form Recognizer team is working on a feature to allow user just submit the document and it would pick the most appropriate model to analyze the document. Please stay tuned for our update.
thanks
I am creating Azure ML experienment to predict multiple values. but in azure ml we can not train a model to predict multiple values. my question is how to bring multiple trained models in single experienment and create webout put that gives me multiple prediction.
You would need to manually save the trained models (right click the module output and save to your workspace) from your training experiment and then manually create the predictive experiment unlike what is done in this document. https://learn.microsoft.com/en-us/azure/machine-learning/studio/walkthrough-5-publish-web-service
Regards,
Jaya
I went through their github files as well as the official site, I can't find the named entity tagging training corpus they used in splotlight.
How Can I found the dataset instead of a trained model?
see This link https://github.com/dbpedia-spotlight/dbpedia-spotlight/wiki/Web-service
In here, method for setting up dbpedia lookup offline is explained. Also they have given 4 tar files which are
redirects_en.nt
short_abstracts_en.nt
instance_types_en.nt
article_categories_en.nt
these are supposed to be training data for it.