ContentDetectorFunction (updated) — support for Information
DimensionReducerFunction(updated) ▪ FeatureExtractorFunction(updated)
FindClusters (updated) — support for fixed number of clusters and UpTo
ClusterClassify(updated) ▪ ClusteringComponents(updated)
Interpretable Machine Learning
FeatureValueImpactPlot — plots the impact of a feature on a model result
FeatureImpactPlot — plots the impact of each feature together
CumulativeFeatureImpactPlot — plots the cumulative impact of each feature
FeatureValueDependencyPlot — plots the result dependency on a feature value
Network Layers »
ReplicateLayer (updated) — support for integer arrays
RandomArrayLayer (updated) — support for more statistical distribution
AttentionLayer (updated) — support for dropout and local masking
ElementwiseLayer (updated) — new activations "Mish" and "GELU"
ThreadingLayer(updated) ▪ FunctionLayer(updated)
Network Training »
NetTrain (updated), LossFunction (updated) — support for multi-output and nonscalar loss
Encoders & Decoders »
"Image" (updated) — resampling and padding support
"Class" (updated) — support for top-k and top-p sampling (nucleus sampling)
Formats
"ONNX" (updated) — export support for net operators
The results were Mathematica failed to solve 1,523 problems, Sympy failed to solve 48,529.
So it has some catching up to do.