Visual Category Theory Brick by Brick, Part 6
Visual Category Theory Brick by Brick, Part 6
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Visual Category Theory Brick by Brick, Part 6

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Completed on 2020-06-08

About the Book

Category theory abstractions are very challenging to apprehend correctly, require a steep learning curve for non-mathematicians, and, for people with traditional naïve set theory education, a paradigm shift in thinking. The book uses LEGO® to teach category theory. The sixth part covers ideas that require a leap of abstraction: vertical and whisker compositions of natural transformations, identity and isomorphism of functors, equivalence, isomorphism, and adjoint equivalence of categories, functor and morphism categories, natural transformations as functors, representable functors, category of presheaves, Yoneda embedding and lemma. It also includes an index for parts 1 - 6.

About the Author

Dmitry Vostokov
Dmitry Vostokov

Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist and author. He is the founder of pattern-oriented software diagnostics, forensics and prognostics discipline and Software Diagnostics Institute. Vostokov has also authored more than 50 books on software diagnostics, anomaly detection and analysis, software and memory forensics, root cause analysis and problem solving, memory dump analysis, debugging, software trace and log analysis, reverse engineering and malware analysis. He has more than 25 years of experience in software architecture, design, development and maintenance in a variety of industries including leadership, technical and people management roles. Dmitry also founded Syndromatix, Anolog.io, BriteTrace, DiaThings, Logtellect, OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services) and Software Prognostics. In his spare time, he presents various topics on Debugging TV and explores Software Narratology, its further development as Narratology of Things and Diagnostics of Things (DoT), and Software Pathology. His current areas of interest are theoretical software diagnostics and its mathematical and computer science foundations, application of artificial intelligence, machine learning and data mining to diagnostics and anomaly detection, software diagnostics engineering and diagnostics-driven development, diagnostics workflow and interaction.

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