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Azzzhar's Projects

accepted-paper icon accepted-paper

Welcome to quote our published papers, and the codes have been uploaded.

autoviz icon autoviz

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

awesome-flutter icon awesome-flutter

💗 A curated list of awesome Flutter libraries, tools, tutorials, articles and more.. All you should know about Flutter development!

cms icon cms

Multilingual PHP CMS built with Laravel and bootstrap

collaconfig-tool icon collaconfig-tool

Colla-Config: A stakeholders preferences-based approach for product lines collaborative configuration https://www.sciencedirect.com/science/article/pii/S016412122200262X

computer-science icon computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

devsecops-maturitymodel icon devsecops-maturitymodel

https://owasp.org/www-project-devsecops-maturity-model/ https://www.datadoghq.com/blog/devsecops-maturity-model-self-assessment/ https://www.dynatrace.com/news/blog/devsecops-maturity-model-best-practices/ https://dsomm.owasp.org/ https://www.youtube.com/watch?v=tX9RHZ_O5NU&ab_channel=OWASPOttawa https://github.blog/2020-08-06-achieving-devsecops-m

diagnostic-model-for-predicting-cardiovascular-disease-risk icon diagnostic-model-for-predicting-cardiovascular-disease-risk

The objective of this project is to develop computational algorithm that can accurately detect cardiovascular related diseases. The dataset used in this project was obtained from the publically available UCI repository heart disease dataset. This dataset has been considered the benchmark dataset in the computational cardiovascular space. The features used in the development of this model are considered medically relevant attributes(as indicated in the literature) as they significantly contribute to the progression of cardiovascular disease.

eager icon eager

repository to host Eager research

face-api.js icon face-api.js

JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

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