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I noticed that NimbusML has been archived. As ML.NET evolves will Microsoft be providing a different path to run the platform through Python? A couple of the models in ML.NET are unique and produce …
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Consider this python based prediction server code:
# One time setup
model = Pipeline()
model.load_model('model.zip')
# Numerous multiple calls to predict:
model.predict(data)
###############…
ganik updated
5 years ago
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We do have a sample of [image classification w/ TF](https://github.com/dotnet/machinelearning-samples/blob/b40499b69fddd751f2c582e748f8f1de64497d84/samples/csharp/getting-started/DeepLearning_TensorFl…
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When a model is loaded from disk, the transforms_predictedlabelcolumnoriginalvalueconverter node is not added to the pipeline which causes the output dtype of the `PredictedLabel` column to be `int32`…
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**Describe the bug**
Local and many model automl V1 sample notebooks can fail on the latest Compute Instance.
This includes:
- local-run-classification-credit-card-fraud.ipynb
- auto-ml-forecast…
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I am trying a long-ish to train model; takes about 4 minutes, and I find the absence of any progress reporting unsettling. I think the same progress reporting that is printed in ML.NET prior to PR #92…
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So in ML.NET, we have this class.
https://github.com/dotnet/machinelearning/blob/master/src/Microsoft.ML.FastTree/FastTreeClassification.cs
The corresponding NimbusML learner is called [FastTree…
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**Describe the bug**
When using the mlnet auto-train tool to create a model, and then load that model using NimbusML, an exception is being thrown.
**To Reproduce**
Steps to reproduce the behavio…
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When specifying `split_start='after_transforms'` in `CV.fit()`, the user defined transforms are not split up correctly. See the graph created by the `fit()` call in the code below.
It seems like if…
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@Anipik: We could make a good benchmark for the image processing pipeline.
I'd recommend using the Dog Breeds vs. Fruits dataset which we used in [NimbusML for its image examples](https://docs.micro…