Closed
Description
ML.NET
P0.5
-
Object Detection Support
- Description: Unlike image classification in ML.NET, which provides the high-level API for image classification training via transfer learning, object detection only supports consumption of ONNX and TF models. Thus, we'd like to add support for object detection training. This will also help keep parity with Azure and Local scenarios in Model Builder, since we are currently building out the Azure object detection experience.
-
Update Image Classification API so we can ship GPU training
- Description: Cuda 10.0 is not supported by NVidia anymore. The installer installs a driver that has an invalid signature, which installs a bad graphics driver. Our instructions take the user down a bad path to failure. There are several options we can explore to fix this issue:
- Option A: We can rebuild TF targeting Cuda 10.1 and use the same version of TF.
- Option B: We can upgrade our TF version to one that is already targeting Cuda 10.1
- Option C: Change to PyTorch low-level implementation, which supports Cuda 10.1
P1
- Change Multi-Class Model Output to provide all labels and scores or provide helper
P2
- SoftMax Transform
- We're currently using a custom mapping
- Normalizer Transform
- We're currently using a custom mapping
- I think ML.NET has one but it doesn't do what we need.
- Pixel Format Converter Transform ( 0-255, 0-255, 0-255 ) ->(0-1, 0-1, 0-1)
- We're currently using a custom mapping
alternatively, if the following operator is supported by ExpressionTransformer, the first three custom transform can be replaced.
- Sum ( For SoftMax Transform, the expression that is not supported is
x => exp(x)/sum(exp(x))
- index slice/index selection (for Normalizer Transform), the expression is
x => with(
x[: , 0] = (x[:,0]-mean1)/var1;
x[: , 1] = (x[:,1]-mean2)/var2;
x[: , 2] = (x[:,2]-mean3)/var3;
x)
- Image Resize that doesn't depend on System.Drawing
- System.Drawing isn't supported by UWP apps
Customer Hit Issues
P0
- Fix Text Loader - In Progress
AutoML.NET
P0
-
Add AutoML.NET Support for all supported ML.NET Scenarios
- Time Series Forecasting
- Anomaly Detection
- Ranking
-
Improve Text Classification
- Description: Currently, ML.NET only tries the default FeaturizeText transformer which doesn't work that well with free-form strings (it's ok with categories). This can be improved if AutoML.NET tries out multiple text featurizers to find the best one for the user's data and scenario.
P0.5
- Add AutoML.NET Support for
- Object Detection
P1
- Save/Restore AutoML State
- Add More Time
- Resume Training
- Shows trainer's sweeping parameters when iterating.
- Improve Recommendation P1
- Only tries MatrixFactorization and that type requires complete retraining for new items/users.
- Improve Image Classification P1
- Only tries one DNN Type.
- Improve Time Series Forecasting (Once added) P1
- Rolling origin cross validation
- Time Series machinelearning#978
- Rolling Cross-validation for Time-series machinelearning#1026
- Rolling origin cross validation
Customer Hit Issues
P2
- Inspect AutoML parameter choices (Inspect AutoML parameter choices #688)
- A dropdown list to choose what OptimizingMetric to use in AutoML GUI (Feature: A dropdown list to choose what OptimizingMetric to use in AutoML GUI #695)
- [AutoML,CLI,ModelBuilder] Exploration Time vs Epochs + Loss/AUC (Enhancement) ([AutoML,CLI,ModelBuilder] Exploration Time vs Epochs + Loss/AUC (Enhancement) #699)