Would you like to learn The "WHAT" and "HOW-TO" about "Knowledge Map for Unified Domain Analysis?

Our first lecture on "WHAT" and "HOW-TO" is on learning and applying "Knowledge Map for Unified Domain Analysis.

Stable Machine Learning Knowledge Map

Domain Analysis

The Keynote

Stable patterns are widely used in today's software engineering in modeling, and they play a vital role in reducing the cost and condensing the time of software product lifecycles. Nowadays, many existing traditional patterns fail to model the subtle changes in the context of implementing the model. As a result, the reusability of the pattern will significantly decrease. This paper aims to present a pattern language for building a core knowledge of stable patterns called a knowledge map. This paper will also represent the first attempt towards a machine learning knowledge map representation via regular patterns to discover, organize, and utilize machine learning core knowledge. Each stable pattern focuses on a distinctive activity and provides a way by which this activity can be conducted efficiently. The presented sound analysis and design patterns will give a core knowledge of a stable machine learning domain that is easily extensible, regular through time, and focuses on challenging machine learning of Unified (1) Functional and non-functional Requirements and (2) Unified Design.

https://youtu.be/1rSO4vDEQMs

Please see the details of the 9th Global Webinar here:

https://www.globalscientificguild.com/applied-science/