The base ML.NET framework comes with a variety of numpy alternatives, datatypes for heterogenous (IDataView) and homogenous (VBuffer) data, a variety of transfo

The base ML.NET framework comes with a variety of numpy alternatives, datatypes for heterogenous (IDataView) and homogenous (VBuffer) data, a variety of transforms for data pre-processing, feature extraction (e.g. OneHotCodeEncoding), Missing values, normalization etc. handy for common ML scenarios like classification, regression, recommendation etc. you can find the full list here. Types:https://github.com/dotnet/machinelearning/blob/master/docs/code/IDataViewDesignPrinciples.md https://github.com/dotnet/machinelearning/blob/master/docs/c... Transforms: https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/transforms https://docs.microsoft.com/en-us/dotnet/machine-learning/res...