This edited book brings together research investigating foundational issues relating to the generation and restriction of alternative sets from theoretical and empirical perspectives.
This book features high-quality research papers presented at the International Conference on Computing and Machine Learning (CML 2024), organized by Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India, during April 29 - 30, 2024.
This book features high-quality research papers presented at the International Conference on Computing and Machine Learning (CML 2024), organized by Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India, during April 29 - 30, 2024.
Embrace the Future: Prosper in the Age of AIStep into a world transformed by artificial intelligence, where opportunity and innovation coexist with unprecedented change.
Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects.
Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects.
