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Disruptive Technologies for Big Data and Cloud Applications: Proceedings of ICBDCC 2021

Posted By: AvaxGenius
Disruptive Technologies for Big Data and Cloud Applications: Proceedings of ICBDCC 2021

Disruptive Technologies for Big Data and Cloud Applications: Proceedings of ICBDCC 2021 by J. Dinesh Peter, Steven Lawrence Fernandes, Amir H. Alavi
English | EPUB | 2022 | 880 Pages | ISBN : 9811921768 | 185.7 MB

This book provides a written record of the synergy that already exists among the research communities and represents a solid framework in the advancement of big data and cloud computing disciplines from which new interaction will result in the future. This book is a compendium of the International Conference on Big Data and Cloud Computing (ICBDCC 2021). It includes recent advances in big data analytics, cloud computing, the Internet of nano things, cloud security, data analytics in the cloud, smart cities and grids, etc. This book primarily focuses on the application of knowledge that promotes ideas for solving the problems of society through cutting-edge technologies. The articles featured in this book provide novel ideas that contribute to the growth of world-class research and development. The contents of this book are of interest to researchers and professionals alike.

Let's Make Recommendation Systems Easy with Live Projects

Posted By: ELK1nG
Let's Make Recommendation Systems Easy with Live Projects

Let's Make Recommendation Systems Easy with Live Projects
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 38 lectures (2h 19m) | Size: 923.4 MB

Python, Recommendation Engine, Data Science, Machine Learning, Artificial Intelligence, Natural Language Processing(NLP)

Mathematical Foundations of Big Data Analytics

Posted By: AvaxGenius
Mathematical Foundations of Big Data Analytics

Mathematical Foundations of Big Data Analytics by Vladimir Shikhman
English | PDF,EPUB | 2021 | 274 Pages | ISBN : 3662625202 | 18.6 MB

In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. – mainly in an economic context.

Topics in Rough Set Theory: Current Applications to Granular Computing

Posted By: AvaxGenius
Topics in Rough Set Theory: Current Applications to Granular Computing

Topics in Rough Set Theory: Current Applications to Granular Computing by Seiki Akama
English | EPUB | 2020 | 208 Pages | ISBN : 3030295656 | 14 MB

This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.