Scope
The Machine Learning Handbook provides guidelines on how to create reliable machine learning functions and perform the verification and validation considering the specifics of machine learning development practices.
Guidelines are provided for selecting, preparing, and validating data, as well as for training, testing, and applying machine learning models within a so-called ‘safety cage’ architecture. The handbook focused on data driven approaches with both supervised and unsupervised learning methods.
Attachments
Md5 checksum .pdf-file = 949FFE33C03084CF0ACA6EB686727CD9A
Md5 checksum .docx file = E3711C3CBE130E7A0DAE54ACBD0F48D5