Metaheuristics in Machine Learning: Theory and ApplicationsКНИГИ » ПРОГРАММИНГ
Название: Metaheuristics in Machine Learning: Theory and Applications Автор: Diego Oliva, Essam H. Houssein, Salvador Hinojosa Издательство: Springer Год: 2021 Формат: PDF Страниц: 765 Размер: 19 Mb Язык: English
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Lie Group Machine Learning Название: Lie Group Machine Learning Автор: Fanzhang Li Издательство: de Gruyter Год: 2019 Страниц: 533 Формат: PDF Размер: 14 Mb Язык: English This...
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Metaheuristics in Machine Learning: Theory and Applications 
