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 [Samples](samples) in this project leverage the basic ideas used in [MLOpsPython](https://github.com/microsoft/MLOpsPython).
 While MLOpsPython lays the foundation for operationalizing ML, we aim to provide representative samples and docs to
 
-- provide a sounding startpoint to build a production quality ML solution of certain frameworks such as Tensorflow or Kaldi.
+- provide a sounding startpoint to build a production quality ML solution of certain frameworks such as TensorFlow or Kaldi.
 - demonstrate approaches and techniques for cross-cutting concerns such as unit testing and logging.
 - document how to solve some of the challenges encountered in building ML solutions, such as security, data management,
 local vs. cloud based development and more.