Create Vector, Matrix types and operations to enable linear algebra API

Survey of existing linear algebra libraries within mahout (samsara), spark (sparkML) and flink (flinkML) shows that they all expose local vector, matrix (sparse, dense) and distributed matrix types and operations. We should define these data types and operations within Beam and add this to the BeamML document https://docs.google.com/document/d/17cRZk_yqHm3C0fljivjN66MbLkeKS1yjo4PBECHb-xA/edit#heading=h.n51rhya8bv4f

Imported from Jira [BEAM-478](https://issues.apache.org/jira/browse/BEAM-478). Original Jira may contain additional context.
Reported by: Kam Kasravi.
Subtask of issue #18006

Start by reviewing the BeamML document and the referenced Mahout Samsara, Spark ML, and Flink ML linear algebra APIs, then read the parent issue #18006 and Jira BEAM-478 for scope. Done means Beam has defined local vector and matrix types, sparse and dense variants, distributed matrix types, and their operations, with the BeamML documentation updated.

Written by the indexing model from the issue text.