[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_28":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNzg0MDM","title","Hundred Key Properties and Operations on Matrices","state","published","contactAuthorMethod","email","aboutText","

In almost all domains of human activities using quantitative modelling, the artificial intelligence (AI) is more and more used to perform tasks for human convenience. In particular, in some subtools of AI such as Machine Learning and Deep Leaning, the algorithms use trainable parametric matricial structures to learn the governing equations of data. That means that matrices play a key role in quantitative and numerical modelling nowadays.

Such a context requires from mathematical researchers largely, and from matrices users the need and necessity to have on a single handbook the main characterizations, properties and calculus rules of a nice subdomain of mathematics such as the matricial algebra.

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