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Model Builder - Image classification - shifting from CPU to GPU
I'm trying to classify images based on 14 different categories. Currently I have about 40.000 images, but I'm planning to add more to try and get a better dataset. Initially I have trained my dataset with my CPU and has pretty decent accuracy (90-98% in most cases), but the training and prediction speed is rather slow. Now I'm trying to use my GPU to speed up this task. The speed is amazing when it's training through the model builder, however the accuracy is terrible. I get about 8% accuracy and the expected category isn't even listed in some cases. The only thing I changed is the CPU to GPU in the Model Builder GUI. Is there something I'm missing here? Do I require even more images to get the same results with my GPU vs my CPU? I'm at a loss here so any help would be really appreciated!Machine Learning Community Standup | May 11, 2022
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ML.Net CLI Example Fails
On following the instructions here: https://learn.microsoft.com/en-us/dotnet/machine-learning/tutorials/sentiment-analysis-cli at this step mlnet classification --dataset "yelp_labelled.txt" --label-col 1 --has-header false --train-time 10 I get this error: System.InvalidOperationException: Unable to resolve service for type 'Microsoft.ML.AutoML.IDatasetManager' while attempting to activate 'Microsoft.ML.AutoML.SweepablePipelineRunner'. at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteFactory.CreateArgumentCallSites(Type implementationType, CallSiteChain callSiteChain, ParameterInfo[] parameters, Boolean throwIfCallSiteNotFound) at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteFactory.CreateConstructorCallSite(ResultCache lifetime, Type serviceType, Type implementationType, CallSiteChain callSiteChain) ... ... mlnet --version says 16.15.0 Anyone know what's wrong?Train Machine Learning Models with ML.NET Model Builder on ARM64
Visual Studio 2022 17.3 Preview 2 is now available as a native ARM64 application on Windows 11. This is the first version of Visual Studio that natively supports building and debugging ARM64 apps on ARM-based processors. .NET workloads are one of the prioritized workloads. What is Model Builder? Model Builder is a Visual Studio extension that uses ML.NET, an open-source, cross-platform machine learning framework for .NET developers to train and deploy custom machine learning models into .NET apps. Get started To get started with Model Builder on ARM64 devices: Install ARM64 Visual Studio Enable Model Builder Note: For image classification scenarios, we recommend using Azure since it's not supported for local environments on ARM devices. For more information, see the tutorial on how to train an image classification model in Azure using Model Builder. We want to hear from you Let us know about your experiences. If you have any feedback or issues running Model Builder on ARM, file an issue in the dotnet/machinelearning-modelbuilder GitHub repository.
AutoML
Hi, I was looking for some answers on training. I like how the AutoML works, especially when the parameters are auto tweaked for a better fit. Is there a way to select a specific algorithm and have the automl iterate over that for X minutes, like the autoML wizard but for a specific algorithm? thank you
