When creating some kalman filter code there was a need for Matrix inversion...
Installing external code to calculate inverses was clunky and painful. Hence this little trait. It's 'reasonably' quick for small Matrices, a dedicated library, even on a CPU is ~5x faster for bigger Matrices, as you would expect. Relatively small matrices / infrequent need for inverses are the use case here. With huge matrices for Machine Learning, you would be using iterative/approximate methods anyway, such as gradient decent.
If your priority is ease of installation, pure Rust and portability then this code might be useful.
Simply reference with:
use ndarray_inverse::Inverse;
Add a cargo dependency too:
ndarray-inverse = "*"
Available methods on Array2 matrices are m.inv() and m.det(). Obviously they must be square matrices.