Machine Learning and Metaheuristic Computation
By Erik Cuevas, Fernando Wario, Jorge Galvez, Omar Avalos | Publisher: Wiley
About the book
Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approaches
Few areas of technology have greater potential to revolutionize the globe than artificial intelligence. Two key areas of artificial intelligence, machine learning and metaheuristic computation, have an enormous range of individual and combined applications in computer science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both.
Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge artificial intelligence tools.
The text also provides:
- Treatment suitable for readers with only basic mathematical training
- Detailed discussion of topics including dimensionality reduction, clustering methods, differential evolution, and more
- A rigorous but accessible vision of machine learning algorithms and the most popular approaches of metaheuristic optimization
Machine Learning and Metaheuristic Computation is ideal for students, researchers, and professionals looking to combine these vital methods to solve problems in optimization approaches.
Editions of Machine Learning and Metaheuristic Computation
- Hardcover
- ISBN 9781394229642
- EBook
- ISBN 9781394229673
- EBook
- ISBN 9781394229680
- EBook
- ISBN 9781394229666
Read an Excerpt
Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approaches
Few areas of technology have greater potential to revolutionize the globe than artificial intelligence. Two key areas of artificial intelligence, machine learning and metaheuristic computation, have an enormous range of individual and combined applications in computer science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both.
Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge artificial intelligence tools.
The text also provides:
- Treatment suitable for readers with only basic mathematical training
- Detailed discussion of topics including dimensionality reduction, clustering methods, differential evolution, and more
- A rigorous but accessible vision of machine learning algorithms and the most popular approaches of metaheuristic optimization
Machine Learning and Metaheuristic Computation is ideal for students, researchers, and professionals looking to combine these vital methods to solve problems in optimization approaches.
Frequently Asked Questions
What is Machine Learning and Metaheuristic Computation about?
Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approaches
Few areas of technology have greater potential to revolutionize the globe than artificial intelligence. Two key areas of artificial intelligence, machine learning and metaheuristic computation, have an enormous range of individual and combined applications in computer science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both.
Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge artificial intelligence tools.
The text also provides:
- Treatment suitable for readers with only basic mathematical training
- Detailed discussion of topics including dimensionality reduction, clustering methods, differential evolution, and more
- A rigorous but accessible vision of machine learning algorithms and the most popular approaches of metaheuristic optimization
Machine Learning and Metaheuristic Computation is ideal for students, researchers, and professionals looking to combine these vital methods to solve problems in optimization approaches.
What core themes, tropes, or subjects are explored in Machine Learning and Metaheuristic Computation?
Computing and Information Technology > Databases / Data management > Data capture and analysis
Where can I read a sample of Machine Learning and Metaheuristic Computation?
You can read an official preview of the few pages here https://www.book2look.com/book/9781394229642
Who is/are the Author/s of the book Machine Learning and Metaheuristic Computation?
Erik Cuevas, Fernando Wario, Jorge Galvez, Omar Avalos
Who is the Publisher of the book Machine Learning and Metaheuristic Computation?
Wiley
What are the ISBN numbers for the physical and digital editions?
Machine Learning and Metaheuristic Computation is available as hardcover(ISBN 9781394229642) and ebook(ISBN 9781394229673) and ebook(ISBN 9781394229680) and ebook(ISBN 9781394229666)
Where can I buy Machine Learning and Metaheuristic Computation online or support local independent bookshops?
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Where can I buy Machine Learning and Metaheuristic Computation?